WO2015051338A1 - Methods and systems for modeling phasing effects in sequencing using termination chemistry - Google Patents

Methods and systems for modeling phasing effects in sequencing using termination chemistry Download PDF

Info

Publication number
WO2015051338A1
WO2015051338A1 PCT/US2014/059191 US2014059191W WO2015051338A1 WO 2015051338 A1 WO2015051338 A1 WO 2015051338A1 US 2014059191 W US2014059191 W US 2014059191W WO 2015051338 A1 WO2015051338 A1 WO 2015051338A1
Authority
WO
WIPO (PCT)
Prior art keywords
nucleic acid
sequencing
tfr
estimated
molecules
Prior art date
Application number
PCT/US2014/059191
Other languages
French (fr)
Inventor
Christian Koller
Marcin Sikora
Peter Vander Horn
Original Assignee
Life Technologies Corporation
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Life Technologies Corporation filed Critical Life Technologies Corporation
Priority to JP2016519836A priority Critical patent/JP6532456B2/en
Priority to EP14790898.2A priority patent/EP3053072B1/en
Priority to CN201480054627.3A priority patent/CN105683980B/en
Publication of WO2015051338A1 publication Critical patent/WO2015051338A1/en

Links

Classifications

    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B40/00ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
    • G16B40/10Signal processing, e.g. from mass spectrometry [MS] or from PCR
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B20/00ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B20/00ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
    • G16B20/20Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B25/00ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B30/00ICT specially adapted for sequence analysis involving nucleotides or amino acids
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B5/00ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
    • CCHEMISTRY; METALLURGY
    • C12BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12QMEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6869Methods for sequencing

Definitions

  • This application generally relates to methods, systems, and computer readable media for nucleic acid sequencing, and, more particularly, to methods, systems, and computer readable medium for modeling phasing effects in nucleic acid sequencing.
  • Nucleic acid sequencing in which the order of nucleotides in a nucleic acid molecule is determined, has become ubiquitous in a wide variety of medical applications, such as biological research, genetic testing, and so forth.
  • One type of sequencing utilized in such applications is sequencing-by- synthesis in which the order of nucleotides in a nucleic acid strand is determined by synthesizing a corresponding strand.
  • sequencing-by- synthesis is a high throughput method employed in many current platforms, there are several drawbacks associated with its use. For example, sequencing-by- synthesis platforms generate large volumes of sequencing data that must subsequently be processed to determine the order of the nucleotides in a given nucleic acid strand.
  • the sequencing data obtained via these methods may include a variety of errors, such as loss of phase synchrony (i.e., loss of synchronous synthesis of the identical templates), that hinder the ability to make accurate base calls. Accordingly, there exists a need for systems and methods that address these issues and enable more accurate and efficient handling of the large volumes of sequencing data obtained via the sequencing-by- synthesis platforms. Docket No. LT00861 PCT
  • Exemplary embodiments of the present disclosure may solve one or more of the above- mentioned problems and/or may demonstrate one or more of the above-mentioned desirable features. Other features and/or advantages may become apparent from the description that follows.
  • a method for nucleic acid sequencing includes receiving observed or measured nucleic acid sequencing data from a sequencing instrument configured to receive a sample nucleic acid and to process the sample nucleic acid in a termination sequencing-by- synthesis process.
  • the method also includes generating a set of candidate sequences of bases for the observed or measured nucleic acid sequencing data by determining a predicted signal for candidate sequences using a simulation framework for simulating possible state transitions for active and inactive molecules present at a K-th base during an N-th nucleotide flow, where K and N denote indices associated with bases and nucleotide flows, respectively.
  • the simulation framework for simulating the possible state transitions incorporates an estimated carry forward rate (CFR), an estimated incomplete extension rate (IER), an estimated droop rate (DR), an estimated reactivated molecules rate (RMR), and an estimated termination failure rate (TFR), the RMR being greater than or equal to zero and the TFR being lesser than one.
  • the method further includes identifying, from the set of candidate sequences of bases, one candidate sequence leading to optimization of a solver function as corresponding to the sequence for the sample nucleic acid.
  • a nucleic acid sequencing system includes a sequencing instrument configured to receive a sample nucleic acid, at least one nucleotide having a terminating group, a primer, and a polymerase, and to process the sample Docket No. LT00861 PCT nucleic acid in a termination sequencing-by- synthesis process to produce raw nucleic acid sequencing data.
  • a processor is configured to receive the raw nucleic acid sequencing data and to generate a set of candidate sequences of bases for sample nucleic acid by determining a predicted signal for candidate sequences using a simulation framework for simulating possible state transitions for active and inactive molecules present at a K-th base during an N-th nucleotide flow, where K and N denote indices associated with bases and nucleotide flows, respectively.
  • the simulation framework for simulating the possible state transitions incorporates an estimated carry forward rate (CFR), an estimated incomplete extension rate (IER), an estimated droop rate (DR), an estimated reactivated molecules rate (RMR), and an estimated termination failure rate (TFR), the RMR being at a value greater than or equal to zero and the TFR being at a value lesser than one.
  • CFR carry forward rate
  • IER estimated incomplete extension rate
  • DR estimated droop rate
  • RMR estimated reactivated molecules rate
  • TFR estimated termination failure rate
  • an apparatus includes a machine readable memory and a processor configured to execute machine -readable instructions, the instructions which when executed cause the apparatus to receive observed or measured nucleic acid sequencing data from a sequencing instrument configured to receive a sample nucleic acid and to process the sample nucleic acid in a termination sequencing-by-synthesis process; and generate a set of candidate sequences of bases for the observed or measured nucleic acid sequencing data by determining a predicted signal for candidate sequences using a simulation framework for simulating possible state transitions for active and inactive molecules present at a K-th base during an N-th nucleotide flow, where K and N denote indices associated with bases and nucleotide flows, respectively.
  • the simulation framework for simulating the possible state transitions incorporates an estimated carry forward rate (CFR), an estimated incomplete extension rate (IER), an estimated droop rate (DR), an estimated reactivated molecules rate Docket No. LT00861 PCT
  • RMR root mean arterial pressure
  • TFR estimated termination failure rate
  • FIG. 1 is a schematic illustrating a sequencing-by- synthesis system, according to an embodiment of the present disclosure.
  • FIG. 2 is a flow chart illustrating a method for identifying a nucleic acid sequence, according to an embodiment of the present disclosure.
  • FIG. 3 is a schematic illustration of a simulation framework for calculating predicted ionograms, according to an embodiment of the present disclosure. Docket No. LT00861 PCT
  • FIG. 4 illustrates an example cell within the simulation framework of FIG. 3 along with possible states and state transitions, according to an embodiment of the present disclosure.
  • FIG. 5 illustrates an example cell within the simulation framework of FIG. 3 along with possible states and state transitions, according to another embodiment of the present disclosure.
  • FIG. 6 illustrates a simplified schematic illustration of a simulation framework for calculating predicted ionograms, according to an embodiment of the present disclosure
  • FIG. 7 illustrates an example cell within the simulation framework of FIG. 6 along with possible states and state transitions, according to an embodiment of the present disclosure.
  • FIG. 8 illustrates a simplified schematic illustration of a simulation framework for calculating predicted ionograms, according to an embodiment of the present disclosure.
  • FIG. 9 illustrates an example cell within the simulation framework of FIG. 8 along with possible states and state transitions, according to an embodiment of the present disclosure.
  • FIGS. 10A-10D illustrate a simulated comparison of standard phasing and terminator phasing for a low noise level, according to an embodiment of the present disclosure.
  • FIGS. 11A-11D illustrate a simulated comparison of standard phasing and terminator phasing for a medium noise level, according to an embodiment of the present disclosure.
  • FIGS. 12A-12D illustrate a simulated comparison of standard phasing and terminator phasing for a high noise level, according to an embodiment of the present disclosure.
  • FIGS. 13A-13H illustrate simulated results for an incomplete extension rate of 0.5% in a termination chemistry sequencing-by- synthesis process, according to an embodiment of the present disclosure.
  • FIGS. 14A-14H illustrate simulated results for an incomplete extension rate of 1.5% in a termination chemistry sequencing-by- synthesis process, according to an embodiment of the present disclosure.
  • FIGS. 15A-15H illustrate simulated results for an incomplete extension rate of 2.5% in a termination chemistry sequencing-by- synthesis process, according to an embodiment of the present disclosure.
  • FIGS. 16A-16H illustrate simulated results for an incomplete extension rate of 3.5% in a termination chemistry sequencing-by- synthesis process, according to an embodiment of the present disclosure.
  • FIGS. 17A-17H illustrate simulated results for an incomplete extension rate of 4.5% in a termination chemistry sequencing-by- synthesis process, according to an embodiment of the present disclosure.
  • grammatical variants are intended to be non-limiting, such that recitation of items in a list is not to the exclusion of other like items that can be substituted or added to the listed items.
  • the present disclosure contemplates systems, methods, and computer readable media for evaluating sample nucleic acid sequences, including making base calls by processing and/or analyzing nucleic acid sequencing data that may be tainted by the presence of phasing effects capable of causing sequencing errors in a sequencing-by- synthesis process that utilizes termination chemistry.
  • a solution to the sequencing problem of identifying the sequence of bases in a nucleic acid sample may be found by minimizing a distance (e.g. , through a least squares fit Docket No.
  • the solution to the minimization problem may be identified by searching or traversing possible sequences with a tree -based solver.
  • various exemplary embodiments of the present disclosure may enable base calls to be made by taking into account one or more phasing effects without the need to remove or correct for such phasing effects.
  • the one or more phasing effects arising in the termination sequencing-by- synthesis process are captured as parameters that are estimated and provided as inputs to the phasing model.
  • the parameters may be chosen to account for a variety of phasing errors that occur due to asynchronous synthesis among identical templates of the nucleic acid molecule to be sequenced.
  • the phasing model may incorporate parameters for incomplete extension, carry forward, droop, reactivated molecules, termination failure, and/or inactivated molecules. In this way, various exemplary embodiments may reduce or eliminate the likelihood that incorrect bases are called due to one or more phasing effects present in a termination chemistry sequencing-by-synthesis process.
  • FIG. 1 illustrates a nucleic acid sequencing system 10 capable of determining an order of nucleotides present in a nucleic acid sample.
  • Polynucleotides may include the natural deoxyribonucleosides (e.g., deoxyadenosine, deoxycytidine, deoxyguanosine, and
  • deoxythymidine for DNA or their ribose counterparts for RNA linked by phosphodiester linkages.
  • they may also include non-natural nucleotide analogs, e.g., including modified bases, sugars, or internucleosidic linkages.
  • LT00861 PCT polynucleotide may be represented by a sequence of letters (upper or lower case), such as "ATGCCTG,” and it will be understood that the nucleotides are in 5' ⁇ 3' order from left to right and that "A” denotes deoxyadenosine, “C” denotes deoxycytidine, “G” denotes deoxyguanosine, and “T” denotes deoxythymidine, and that "I” denotes deoxyinosine, and "U” denotes deoxyuridine, unless otherwise indicated or obvious from context.
  • A denotes deoxyadenosine
  • C denotes deoxycytidine
  • G denotes deoxyguanosine
  • T denotes deoxythymidine
  • I denotes deoxyinosine
  • U denotes deoxyuridine
  • the nucleic acid sequencing system 10 includes a control and processing system 12 that receives nucleic acid sequencing data from a sequencing instrument 14 for analysis and/or processing.
  • the sequencing instrument 14 is configured to perform a sequencing-by-synthesis process using termination chemistry ("termination sequencing-by- synthesis").
  • termination sequencing-by- synthesis encompasses all sequencing-by- synthesis processes that employ any type of termination chemistry.
  • termination sequencing- by-synthesis includes, but is not limited to, sequencing-by- synthesis processes in which nucleic acid replication is reversibly or irreversibly terminated in a stepwise fashion via incorporation of one or more terminators, such as chemically altered dNTPs (e.g.
  • ddNTPs dideoxynucleotides
  • One or more materials 16 are provided in various concentrations under control of flow controller 18.
  • the materials include nucleic acid polymerase 20, nucleic acid primer 22, nucleic acid template 24, deoxyrobonucleotides (dNTP(s)) (e.g. , dATP, dCTP, dGTP, dTTP) 26, and 2 * ,3 * dideoxynucleotides (ddNTPs) (e.g. , ddATP, ddCTP, ddGTP, ddTTP) 28, although as discussed in detail below, the materials 16 provided for a given application may vary, for example, depending on implementation- specific considerations. Docket No. LT00861 PCT
  • the illustrated embodiment of the control and processing system 12 includes an internal bus 30 to which a processor 32 is connected to enable communication with a variety of other system components.
  • Control and processing system 12 also includes a random access memory (RAM), or other dynamic memory, coupled to bus 30 for storing instructions to be executed by the processor 32.
  • the RAM 34 may also be used for storing temporary variables or other intermediate information during execution of instructions to be executed by the processor 32.
  • ROM read only memory
  • the control and processing system 12 may also include a storage device 38, such as a magnetic disk, optical disk, or solid state drive (SSD) for storing information or instructions.
  • the storage device 38 may include a media drive and a removable storage interface.
  • a media drive may include a drive or other mechanism to support fixed or removable storage media, such as a hard disk drive, a floppy disk drive, a magnetic tape drive, an optical disk drive, a CD or DVD drive (R or RW), flash drive, or other removable or fixed media drive.
  • the storage device 38 may further include a computer-readable storage medium having stored therein particular computer software, instructions, or data.
  • the control and processing system 12 may also include a communications interface 40 that enables software and/or data to be transferred between computing system the control and processing system 12 and one or more external devices.
  • communications interface 40 include a modem, a network interface (such as an Ethernet or other NIC card), a
  • communications port such as for example, a USB port, a RS-232C serial port), a PCMCIA slot and card, Bluetooth, and the like.
  • Software and data transferred via the communications interface 40 may be in the form of signals, which can be electronic, electromagnetic, optical or other signals capable of being received by communications interface 40. These signals may be Docket No. LT00861 PCT transmitted and received by communications interface 40 via a channel, such as a wireless medium, wire or cable, fiber optics, or other communications medium.
  • One or more control inputs 42 may be communicated to the processor 32 via the communications interface 40.
  • Control inputs 42 may be provided via one or more input devices, such as a keyboard, an interactive display, such as an LCD display configured with touch screen input capabilities, a cursor control, such as a mouse, and so forth.
  • the processor 32 may also be coupled via bus 30 to a display 44, such as a cathode ray tube (CRT) or liquid crystal display (LCD), for displaying information to a user.
  • a display 44 such as a cathode ray tube (CRT) or liquid crystal display (LCD)
  • the sequencing instrument 14 performs a termination sequencing-by-synthesis process, thereby generating raw data
  • nucleic acid sequencing system 10 corresponding to an incorporation signal indicative of one or more nucleotide incorporations into a nucleic acid strand being synthesized in the sequencing operation.
  • nucleic acid polymerase 20, nucleic acid primer 22, a nucleic acid template 24 to be sequenced, dNTP(s) 26, and ddNTP(s) 28 are provided as inputs to the sequencing instrument 14 for use in the termination sequencing-by- synthesis process.
  • the particular type, mixture, and timing of the reactants provided to the sequencing instrument 14 will vary depending on a variety of implementation- specific considerations, such as the type of sequencing-by-synthesis method being employed, the type of termination chemistry used, the available imaging or sensing platforms, and so forth. Accordingly, the materials 16 shown in FIG. 1 are non-limiting examples of the types of reactants that could be provided to the sequencing instrument. Docket No. LT00861 PCT
  • the terminator provided to the sequencing instrument 14 may include any of a variety of classes of terminators suitable for terminating primer extension.
  • suitable terminators include irreversible terminators, such as ddNTPs that lack a 3' hydroxyl and, thus, interrupt nucleic replication by virtue of a hydrogen instead of a hydroxyl at the 3' position.
  • reversible terminators also may be utilized.
  • Such terminators may include 3'-0-blocked reversible terminators and 3 '-unblocked reversible terminators.
  • Suitable 3'-0-blocked reversible terminators may include a terminating group linked to the oxygen atom of the 3' hydroxyl of the pentose.
  • terminators of this type may be utilized in different implementations, including but not limited to 3'-ONH 2 reversible terminators, 3'-0-allyl reversible terminators, and 3'-0- azidomethy reversible terminators.
  • Suitable 3 '-unblocked reversible terminators include an intact 3' hydroxyl group and a terminating group linked to the base for termination of primer extension.
  • terminators of this type may be utilized in different implementations, including but not limited to the 3' -OH unblocked reversible terminator named “virtual terminator” and the 3' -OH unblocked nucleotides termed “Lightening TerminatorsTM,” which have a terminating 2-nitrobenzyl moiety attached to hydroxymethylated nucleobases.
  • the particular polymerase 20 selected for use in the processes performed by the sequencing instrument 14 may vary. That is, the type of nucleotide analog selected for the nucleic acid sequencing may impact the type of DNA polymerase 20 that will yield the optimal efficiency.
  • the Lightening TerminatorsTM may be selected for use as the terminator, and the TherminatorTM DNA polymerase developed for use with the Lightening TerminatorsTM may be utilized to optimize efficiency. Docket No. LT00861 PCT
  • the order and mixture of the dNTPs 26 and/or the ddNTPs 28 may be varied by the flow controller 18.
  • the flow controller 18 may regulate a reaction including all four of the ddNTPs 28 (i.e. , ddATP, ddCTP, ddGTP, ddTTP), each coupled to a different color fluorescent marker to enable identification, for example, via a fluorescent based imaging system.
  • the sequencing instrument 14 may be configured to perform electronic or charged-based nucleic acid termination sequencing-by- synthesis.
  • an incorporation signal generated from a nucleotide incorporation event may be determined by detecting ions (e.g. , hydrogen ions) that are generated as natural by-products of polymerase-catalyzed nucleotide extension reactions.
  • sample or template nucleic acid which may be a fragment of a nucleic acid sequence of interest, for example, and which may be directly or indirectly attached as a clonal population to a solid support, such as a particle, microparticle, bead, etc.
  • the sample or template nucleic acid 24 may be operably associated to a primer 22 and polymerase 20.
  • the template nucleic acid 24 may be subjected to repeated cycles or "flows" (which may be referred to herein as "nucleotide flows" from which nucleotide incorporations may result with
  • the terminator utilized may be one of the Lightening TerminatorsTM
  • the polymerase may be one of the TherminatorTM DNA polymerase, such as Therminator III.
  • the primer 22 may be annealed to the sample or template 24 so that the primer's 3' end can be extended by a polymerase whenever, for example, ddNTPs 28 complementary to the next base in the template are added. Then, based on the known sequence of nucleotide flows and on measured incorporation signals during each nucleotide flow, the identity of the type, sequence and number of nucleotide(s) associated with a sample nucleic acid 24 present in a reaction chamber can be determined.
  • sequence of nucleotide flows may be based on a cyclical, repeating pattern consisting of consecutive repeats of a short pre-determined cycle of nucleotide flows (e.g., consecutive repeats of pre-determined sequence of four nucleotide flows such as, for example, "ACTG ACTG. . .”); may be based in whole or in part on some other pattern of nucleotide flows (such as, e.g., any of the various nucleotide flow orders discussed or contemplated in Hubbell et al., U.S. Pat. Appl. Publ. No. 2012/0264621, published October 18, 2012); or may also be based on some combination thereof.
  • the four different kinds of ddNTPs are added sequentially to the reaction chambers, so that each reaction is exposed to the four different ddNTPs, one at a time.
  • the four different kinds of ddNTPs are added in the following sequence: ddATP, ddCTP, ddGTP, ddTTP, ddATP, ddCTP, ddGTP, ddTTP, etc., with each exposure followed by a wash step.
  • each exposure to a ddNTP followed by a washing step can be considered a "nucleotide flow.”
  • Four consecutive nucleotide flows can be considered a "cycle.”
  • a two cycle nucleotide flow order can be represented by: ddATP, ddCTP, ddGTP, ddTTP, ddATP, ddCTP, ddGTP, ddTTP, with each exposure being followed by a wash Docket No. LT00861 PCT step.
  • each nucleotide flow may lead to a single nucleotide incorporation before primer extension is terminated.
  • FIG. 2 illustrates an embodiment of a method 50 for identifying a nucleic acid sequence of a DNA template.
  • the method 50 includes receiving raw data in the form of measured or observed data obtained via a sequencing operation (block 52).
  • raw data may be received by the processor 32 of the control and processing system 12 from the sequencing instrument 14 after running a termination sequencing-by-synthesis process.
  • the processor 32 may include a solver configured to transform the raw data received at block 52 into a base call and compile consecutive base calls associated with a sample nucleic acid template into a read, with each base call referring to a particular nucleotide identification (e.g. , dATP ("A"), dCTP ("C”), dGTP ("G”), dTTP ('?')).
  • A dATP
  • C dCTP
  • GTP dGTP
  • dTTP dTTP
  • a phasing model may be generated to model the phasing effects that can occur in the termination sequencing-by- synthesis process and enable such phasing effects to be taken into account when processing or analyzing the raw data to determine the base calls.
  • an estimate of one or more of six parameters may be estimated at blocks 54, 56, 58, 60, 62, and 64.
  • the method 50 can include obtaining an estimate for a carry forward rate (CFR) (block 54).
  • the CFR may be a parameter that encompasses plus frame shifts and corresponds to the rate at which nucleic acid copies incorporate a nucleotide different from the one flown in a given flow cycle.
  • the method 50 also can include obtaining an estimate of an incomplete extension rate (IER) (block 56).
  • the IER may be a parameter that encompasses minus frame shifts and corresponds to the rate at which nucleic acid copies fail to extend during a flow cycle.
  • the Docket No. LT00861 PCT method 50 further can include obtaining an estimate of a droop rate (DR) (block 58), which corresponds to a rate at which active nucleic acid copies become inactive during a cycle. The transition from active to inactive may occur, for example, due to incomplete removal of a terminating group or polymerase inactivation.
  • DR droop rate
  • the method 50 can include obtaining an estimate for a reactivated molecules rate (RMR) (block 60).
  • RMR reactivated molecules rate
  • the RMR corresponds to the rate at which inactive nucleic acid copies become reactivated at a later point in time than intended. This parameter may encompass instances in which a terminating group was previously left intact and removed at a later time.
  • the method 50 can include obtaining an estimate for a termination failure rate (TFR) (block 62).
  • TFR corresponds to the rate at which phasing errors occur due to ineffective termination of primer extension.
  • the TFR may include the rate at which the terminating group fails to prevent the polymerase from recognizing the 3' hydroxyl group and an additional nucleotide is therefore incorporated.
  • the TFR may also include the rate at which the other types of terminators described in detail above fail to terminate primer extension and the rate at which a given polymerase fails to discriminate the terminating group at the 3' location, thus incorporating additional nucleotides.
  • the method 50 can include obtaining an estimate for inactivated molecules rate (IMR) (block 64).
  • IMR inactivated molecules rate
  • the IMR corresponds to the rate at which nucleic acid copies become inactive after they have incorporated a base and after the corresponding incorporation signal has been detected.
  • Such inactivation may occur, for example, due to the use of irreversible terminators or due to a general failure of reverse termination when reversible terminators are used.
  • the method 50 includes generating a set of candidate sequences by simulating possible molecule state transitions for active and inactive molecules at each flow and base (block 66) and identifying which sequence of the generated set of sequences optimizes a solver function (block 68).
  • a solver may be configured as a software tool or application with functionality to efficiently solve or determine, from a set of possible or candidate sequences of bases, which sequence is in some sense most consistent with some observed or measured raw data. Possible or candidate sequences may be evaluated by predicting data that would be expected for such sequences under one or more predictive models
  • Y represent observed or measured data (e.g., a vector of values such as an observed or measured ionogram or flowgram, for example, or other sequencing values)
  • X represent predicted data (e.g., a vector of values such as a predicted ionogram or flowgram)
  • A represents a set of possible or candidate nucleic acid or base sequences (e.g., the set comprising the possible sequences of A, C, G, and T; the set comprising the possible sequences of A, C, G, and T that have at most a certain length; or any other subset of candidate sequences)
  • P represent a set of parameters used by the one or more predictive models (e.g., one or more of the parameters for the incomplete extension, carry-forward, droop, reactivated molecules, termination failure rates, inactivation rates).
  • the solver may be thought of as a function / that determines for some defined space or reaction confinement Docket No. LT00861 PCT regions comprising one or more sample nucleic acids a "best" candidate sequence A* from set A such that
  • a * f ⁇ Y, X(A, P)) ⁇ g AiP mm D (Y - X(A, where min f (x, y) generally denotes the value (or values) of x and y that would generally minimize the function /(x,y) and where D(y-x) denotes some function of the "distance" between y and x (e.g., a sum of squared distances or any other measure of a distance between vectors, for example).
  • Such a solver may in principle consider the possible combinations of sequences in set A and values for the parameters in set P to identify an optimal combination of a sequence and parameter values.
  • the search may advantageously be limited to a subset of sequences and subset of candidate values for the parameters.
  • the search may be facilitated by performing parameter estimation (e.g. , as in blocks 54, 56, 58, 60, 62, and 64 of FIG. 2) separately from the optimization, dividing the process into two phases. For example, in a first step, the parameters may be estimated, and in a second step, the parameter estimates may be treated as fixed and supplied as inputs to the solver problem, which could then be reformulated as
  • an optimal sequence A* may be found as follows: First, estimates of IER, CFR, DR, RMR, and TFR may be obtained using any suitable method. Reference is made to Davey et al., U.S. Patent No. 8,666,678, filed Oct. 27, 2011, and in Davey et al., U.S. Publication No. 2014/0051584, filed Aug.
  • one or more of the parameters may be estimated separately for each cell in a dynamic programming matrix (e.g., for each cell in matrix 70, 120, and/or 130 described below), thereby resulting in variations in the estimated parameters across cells of a given matrix.
  • one or more of the parameters may be set at a fixed estimation value for a given row in the dynamic programming matrix while one or more of the remaining parameters in different columns of the matrix vary from cell to cell.
  • the parameter estimations for each of the cells of a matrix may vary in a variety of suitable manners, depending on the given implementation.
  • A* arg A min D (Y— X(A ⁇ IER, CFR, DR, RMR, TFR) ), where X(AIP) denotes X as a function of A given some fixed parameters P (e.g., IER, CFR, DR, RMR, and TFR in this example).
  • P e.g., IER, CFR, DR, RMR, and TFR in this example.
  • Any suitable optimization method may be used to solve this Docket No. LT00861 PCT problem, such as using a tree-based solver.
  • the foregoing approach can be applied using a different number or combination of the six parameters described above and the five above should be understood to be one non-limiting exemplary illustration.
  • a subset of the six disclosed parameters may be utilized.
  • three parameters, IER, CFR, and DR may be utilized with a termination sequencing-by-synthesis process.
  • four parameters may be utilized, for example, combining IER, CFR, DR, and RMR with TFR set to zero, or combining IER, CFR, DR, and TFR, with RMR set to zero.
  • the preceding five parameters may be incorporated into the model with RMR and TFR both set at values greater than zero, but with TMR less than 1.
  • Yet another embodiment in which irreversible terminators are utilized may incorporate all of the six disclosed parameters, including IER, CFR, DR, TFR, RMR, and IMR.
  • the possible permutations of the parameter models provided herein enables the phasing models according to various exemplary embodiments to be applicable across a variety of sequencing platforms, including platforms that do not utilize termination chemistry.
  • the five parameter model described above may collapse to a three parameter model by setting RMR to zero and TFR to one, as described in more detail below.
  • FIGS. 3-9 illustrate exemplary embodiments of simulation frameworks and matrices that can be utilized to calculate predicted ionograms.
  • the particular simulation framework and matrix chosen for a given application may depend on a variety of implementation- specific considerations and factors, such as, for example, the type of termination chemistry being utilized in the sequencing-by-synthesis process.
  • FIGS. 3 and 4 illustrate a simulation framework and matrix, respectively, which may be utilized to calculate predicted ionograms in a Docket No. LT00861 PCT termination sequencing-by-synthesis process utilizing, for example, reversible terminators as disclosed above.
  • FIGS. 3 and 5 illustrate a simulation framework and matrix, respectively, which may be utilized to calculate predicted ionograms in a termination sequencing-by-synthesis process utilizing, for example, irreversible terminators as disclosed above.
  • FIG. 3 illustrates schematically a simulation framework 70 for calculating predicted ionograms, according to an embodiment of the present invention.
  • the representation includes various steps and can be thought of as a matrix of the nucleotide flows (e.g. , columns representing flows 1, 2, 3, and so on) and nucleotide bases (e.g. , rows representing bases 1, 2, 3, and so on). Bases may or may not incorporate during a particular intended flow, and moreover may incorporate during unintended flows, as described in further detail below. Simulations of intended incorporations, incorporation failures, and/or unintended incorporations generate paths along the cells of such a matrix.
  • FIG. 4 illustrates an exemplary cell 80 within the matrix illustrated in FIG. 3, with possible molecule states and state transitions labeled, according to one disclosed embodiment.
  • a cell illustrates what may happen for active molecules (e.g. , a molecule being actively synthesized during a flow with an active polymerase) and inactive molecules present at the K-th base during the N-th nucleotide flow in parameter phasing model incorporating the five parameters, IER, CFR, DR, RMR, and TFR.
  • a phasing model may be useful in a termination sequencing-by-synthesis platform that uses reversible terminators, for example.
  • active molecules include those that either incorporated base K-1 in flow N or Docket No. LT00861 PCT did not incorporate base K in flow N-1.
  • Inactive molecules include molecules that incorporated K-l bases in N-1 flows.
  • arriving at juncture 86 is the sum of the active molecules (Qi' , Q 2 , and Q 6 ') in cell 80.
  • the active molecules may fail to extend or undergo incomplete extension, which subset Q8 is passed to juncture 89; they may become inactive and undergo droop, which subset Q 5 is passed to juncture 90; or they may undergo normal extension or a carry forward event and incorporate base K in flow N, which subset of molecules Q 4 becomes active molecules that have incorporated base K in flow N and move to the next cell along a flow column N.
  • transition factors are [TFR], [1- TFR], [RMR], and [IER x (1 - DR)], respectively.
  • Q 4 may be determined directly or indirectly from prior states based on three transition factors ([TFR], [RMR], and ([1 - IER] x [1 - DR])).
  • Q 7 may be determined directly or indirectly from prior states based on four transition factors ([TFR], [RMR], (1 - [RMR]), and [DR]).
  • the proportion of molecules that will remain active and not incorporate base K in flow N may be determined by multiplying some measure of the quantity (e.g., number,
  • the proportion of molecules that will remain active and incorporate base K in flow N may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the active prior states by the Docket No. LT00861 PCT corresponding transition factor (e.g., multiplying (Qi '+(3 ⁇ 4+(3 ⁇ 4' ) by a transition factor
  • the proportion of molecules that will be inactive having incorporated K- 1 bases in N flows may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the prior active or inactive states reaching the transition by the corresponding transition factors and adding the resulting quantities (e.g., multiplying
  • Q 3 may be determined directly or indirectly from prior states based on four transition factors that are based on the five parameters. Those factors are [TFR], [1- TFR], [RMR], and [(1 - CFR M ) + CFR M x IER x (1 - DR)])].
  • Q 4 may be determined directly or indirectly from prior states based on three transition factors ([TFR], Docket No. LT00861 PCT
  • the proportion of molecules that will remain active and not incorporate base K in flow N may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the prior active states by the corresponding transition factors and adding the resulting quantities (e.g., multiplying (Qi'+C +Qe') by a transition factor comprising term
  • the proportion of molecules that will remain active and incorporate base K in flow N may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the active prior states by the corresponding transition factor (e.g., multiplying (Qi'+Q 2 +Q 6 ') by a transition factor comprising term [CFR M x(l-IER)x(l-DR)] to obtain Q 4 ).
  • the proportion of molecules that will be inactive having incorporated K-l bases in N flows may be determined by combining the quantities (e.g., number, concentration, etc.) of molecules in the prior states by the corresponding transition factors and adding the resulting quantities (e.g., multiplying (Qi'+Q 2 +Q 6 ') by a transition factor [CFR M xDR] to obtain Q 5 and multiplying Q 6 by a transition factor [1-RMR] to obtain Q 6 ", and adding Q 5 and Q 6 " to obtain Q 7 ).
  • the quantities e.g., number, concentration, etc.
  • adding the resulting quantities e.g., multiplying (Qi'+Q 2 +Q 6 ') by a transition factor [CFR M xDR] to obtain Q 5 and multiplying Q 6 by a transition factor [1-RMR] to obtain Q 6 ", and adding Q 5 and Q 6 " to obtain Q 7 ).
  • FIG. 5 illustrates an exemplary cell 110 within the matrix illustrated in FIG. 3, with possible molecule states and state transitions labeled, according to another exemplary in which a sixth parameter is incorporated into the phasing model described in detail above.
  • This additional parameter is an inactivated molecules rate (IMR) and corresponds to the rate at which the molecules are inactivated, which may be useful in an implementation that uses irreversible terminators or when the reversal process of reversible terminators is imperfect.
  • IMR inactivated molecules rate
  • the exemplary cell 110 illustrates what may happen for active molecules (e.g. , a molecule being actively synthesized during a flow with an active polymerase) and inactive molecules present at the K-th base during the N-th nucleotide flow in the six parameter model incorporating the IMR.
  • active molecules include those that either incorporated base K-l in flow N or did not incorporate base K in flow N-1.
  • Inactive molecules include molecules that incorporated K- l bases in N- 1 flows.
  • the Qi ' subset are passed to juncture 86, where they may then undergo one of three possibilities within cell 80 (i.e., at the Kth base for flow N), the Qi" subset is passed to juncture 89, and the Qi ' " subset is passed to juncture 84.
  • the active molecules that enter cell 80 due to a failure to incorporate base K in the N-1 flow is represented by Q 2 in FIG. 5, and this subset of active molecules also is passed to juncture 86 in FIG. 5.
  • arriving at juncture 86 is the sum of the active molecules Q 2 , and Q 6 ') in cell 80.
  • the active molecules may fail to extend or undergo incomplete extension, which subset Q8 is passed to juncture 89; they may become inactive and undergo droop, which subset Q 5 is passed to juncture 90; or they may undergo normal extension or a carry forward event and incorporate base K in flow N, which subset of molecules Q 4 becomes active molecules that have incorporated base K in flow N and move to the next cell along a flow column N.
  • Q 3 may be determined directly or indirectly from prior states using five transition factors based on five of the six parameters, the five transition factors being [IMR], [TFR], [1- TFR-IMR], [RMR], and [IER x (1 - DR)].
  • Q 4 may be determined directly or indirectly from prior states based on transition factors [IMR], [TFR], [RMR], and ([1 - IER] x [1 - DR]).
  • Q 7 may be determined directly or indirectly from prior states based on transition factors [IMR], [TFR], [RMR], (1 - [RMR]), and [DR].
  • the proportion of molecules that will remain active and not incorporate base K in flow N may be determined by multiplying some measure of the quantity (e.g., number,
  • the proportion of molecules that will remain active and incorporate base K in flow N may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the active prior states by the corresponding transition factor (e.g., multiplying (Qi'+C +Qe ) by a transition factor [(l-IER)x(l-DR)] to obtain Q 4 ).
  • the proportion of molecules that will be inactive having incorporated K-1 bases in N flows may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the prior active or inactive states reaching the transition by the corresponding transition factors and adding the resulting quantities (e.g., multiplying (Qi'+C +Qe ) by a transition factor [DR] to obtain Q5 and multiplying (Q6+Q1 ' " ) by a transition factor [1-RMR] to obtain Q 6 ", and adding Q 5 and Q 6 " to Docket No. LT00861 PCT obtain Q 7 ) .
  • some measure of the quantity e.g., number, concentration, etc.
  • the proportion of molecules that will remain active and not incorporate base K in flow N may be determined by multiplying some measure of the quantity (e.g., number,
  • the proportion of molecules that will remain active and incorporate base K in flow N may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the active prior states by the corresponding transition factor (e.g., multiplying (Qi'+C +Qe ) by a transition factor [(CFR M ) x (l-IER)x(l-DR)] to obtain Q 4 ).
  • the proportion of molecules that will be inactive having incorporated K-l bases in N flows may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the prior active or inactive states reaching the transition by the corresponding transition factors and adding the resulting quantities (e.g., multiplying (Qi'+C +Qe ) by a transition factor [CFR M x DR]) to obtain (3 ⁇ 4 and multiplying (Q6+Q1 ' " ) by a transition factor [1- RMR] to obtain Q 6 ", and adding Q 5 and Q 6 " to obtain Q 7 ) .
  • some measure of the quantity e.g., number, concentration, etc.
  • the proportion of molecules that will be inactive having incorporated K-l bases in N flows may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the prior active or inactive states reaching the transition by the corresponding transition factors and adding the resulting quantities (e.g., multiplying (Qi
  • FIG. 6 illustrates schematically a simulation framework 120 for calculating predicted ionograms according to an embodiment in which termination chemistry is not utilized.
  • RMR may be set to zero
  • TFR may be set to one
  • IMR if being used
  • the representation includes various steps and can be thought of as a matrix of flows (columns representing flows 1, 2, 3, and so on) and bases (rows representing bases 1, 2, 3, and so on). Again, bases may or may not incorporate in response to the flows, and simulations of incorporations (or absence thereof) generate paths along the cells of such a matrix.
  • FIG. 7 illustrates an example cell 122 within a matrix as illustrated in FIG. 6, along with possible states and state transitions according to an embodiment.
  • a cell 122 illustrates what may happen for an active molecule (e.g. , polymerase) present at the K-th base during the N-th flow.
  • an active molecule e.g. , polymerase
  • the molecule either incorporated base K-l in flow N or did not incorporate base K in flow N-l .
  • the molecule may undergo normal extension or a carry-forward event, and incorporate base K in flow N.
  • the molecule may also fail to extend or undergo an incomplete extension event, and not incorporate base K in flow N.
  • the molecule may become inactive and thus undergo droop.
  • the proportion of molecules in the possible subsequent states will depend on the incoming populations and state transition parameters.
  • the proportion of molecules that will remain active and not incorporate base K in flow N may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the two prior states (e.g.,
  • the proportion of molecules that will remain active and incorporate base K in flow N may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the two prior states (e.g., Q1+Q2) by a transition factor comprising term [(l-IER)x(l-DR)] .
  • the proportion of molecules that will remain active and not incorporate base K in flow N may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the two prior states Docket No. LT00861 PCT
  • the proportion of molecules that will remain active and incorporate base K in flow N may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the two prior states (e.g., Q1+Q2) by a transition factor comprising term [CFR M x(l-IER)x(l-DR)] .
  • FIG. 8 illustrates schematically a simulation framework 130 for calculating predicted ionograms according to an embodiment in which the RMR rate, the TFR rate, and the IMR rate (if being modeled) are set to zero. By setting these parameters to zero, the dynamic
  • the programming matrix reduces to an upper triangular matrix as shown in FIG. 8.
  • the representation includes various steps and can be thought of as a matrix of flows (columns representing flows 1, 2, 3, and so on) and bases (rows representing bases 1, 2, 3, and so on). Again, bases may or may not incorporate in response to the flows, and simulations of incorporations (or absence thereof) generate paths along the cells of such a matrix.
  • FIG. 9 illustrates an exemplary cell 132 within the matrix illustrated in FIG. 8, with possible molecule states and state transitions labeled, according to one disclosed embodiment.
  • a cell illustrates what may happen for active molecules (e.g. , a molecule being actively synthesized during a flow with an active polymerase) present at the K-th base during the N-th nucleotide flow.
  • active molecules include those that either incorporated base K-l in flow N or did not incorporate base K in flow N-l .
  • the active molecules that incorporated base K-l in flow N (Qi in FIG. 9) are passed to juncture 89.
  • the Docket No. LT00861 PCT active molecules that enter cell 132 due to a failure to incorporate base K in the N-l flow are represented by Q 2 in FIG. 9, and this subset of active molecules is passed to juncture 86 in FIG. 9.
  • the active molecules may fail to extend or undergo incomplete extension, which is represented by Q8 in FIG. 9, and are passed to juncture 89; they may become inactive and undergo droop, which is represented by subset Q5 in FIG. 9; or they may undergo normal extension or a carry forward event and incorporate base K in flow N, which is represented by Q 4 in FIG. 9, which becomes active molecules that have incorporated base K in flow N and move to the next cell along a flow column N.
  • Q 3 may be determined directly or indirectly from prior states based on transition rate [IER x (1 - DR)]
  • Q 4 may be determined directly or indirectly from prior states based on transition rate ([1 - IER] x [1 - DR]).
  • the proportion of molecules that will remain active and not incorporate base K in flow N may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the prior active states by the corresponding transition factors and adding the resulting quantities (e.g., multiplying (Q 2 ) by a transition factor [IERx(l-DR)] to obtain Q 8 , and adding Q 8 and Qi to obtain Q 3 ).
  • the proportion of molecules that will remain active and incorporate base K in flow N (Q 4 ) may be determined by multiplying some Docket No. LT00861 PCT measure of the quantity (e.g., number, concentration, etc.) of molecules in the active prior states by the corresponding transition factor (e.g., multiplying (Q 2 ) by a transition factor
  • Q 3 may be determined directly or indirectly from prior states based on transition factor [(1-CFR M )+CFR M x IER x (1 - DR)]
  • Q 4 may be determined directly or indirectly from prior states based on transition factor ([CFR M ] x [1 - IER] x [1 - DR]).
  • the proportion of molecules that will remain active and not incorporate base K in flow N may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the prior active states by the corresponding transition factors and adding the resulting quantities (e.g., multiplying (Q 2 ) by a transition factor [(1-CFR M )+CFR M x IER x (1 - DR)] to obtain Q 8 , and adding Q 8 and Q l to obtain Q 3 ).
  • the proportion of molecules that will remain active and incorporate base K in flow N may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the active prior states by the corresponding transition factor (e.g., multiplying (Q 2 ) by a transition factor [CFR M x (1 - IER) x (1 - DR)] to obtain Q 4 ).
  • FIGS. 10A-10D, 11A-11D, and 12A-12D illustrate simulated plots showing a
  • FIGS. 10A-10D illustrate plots showing the simulated results for a low noise level (with the noise standard deviations set at 0.03 additive, 0.03 multiplicative);
  • FIGS. 11A-11D illustrate plots showing the simulated results for a medium noise level (with the noise standard deviations set at 0.1 additive, 0.05 multiplicative);
  • FIGS. 12A-12D illustrate plots showing the simulated results for a high noise level (with the noise standard deviations set at 0.2 additive, 0.05 multiplicative).
  • the termination chemistry model when experiencing the same phasing parameters, the termination chemistry model exhibits reduced error rates per flow as compared to the standard model. Further, based on the simulations presented, the termination chemistry models provided herein enable unexpected and significantly greater accuracy in the results for longer homopolymers.
  • FIGS. 10A, 11A, and 12A illustrate an error rate versus homopolymer length for low, medium, and high noise levels, respectively.
  • the termination chemistry error rate is significantly reduced compared to the standard error rate at each of the noise levels.
  • FIGS. 10B, 1 IB, and 12B illustrate an error rate by flow for low, medium, and high noise levels, respectively.
  • the termination chemistry models provided herein enable reduced errors rates per flow.
  • FIGS. IOC, 11C, and 12C illustrate the number of flows it takes to sequence through the template for the low, medium, and high noise levels, respectively.
  • FIGS. 10D, 1 ID, and 12D illustrate the average error rates per base Docket No. LT00861 PCT for the low, medium, and high noise levels, respectively, again showing the reduction in error rates with the termination chemistry model.
  • FIGS. 13A-13H, FIGS. 14A-14H, FIGS. 15A-15H, FIGS. 16A-16H, and FIGS. 17A-17H illustrate simulations comparing termination chemistry modeling and standard modeling for incomplete extension levels of 0.5, 1.5, 2.5, 3.5, and 4.5, respectively.
  • Sets A-D and E-F simulate the same set of base sequences and phasing parameters for different nucleotide flow orders.
  • the noise standard deviations were set at 0.05 additive, 0.05 multiplicative.
  • the termination chemistry model offers improved error rates for longer homopolymer lengths, as can be seen from FIGS. 13A,E, 14A,E, 15,A,E, 16,A,E.

Landscapes

  • Life Sciences & Earth Sciences (AREA)
  • Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Medical Informatics (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Biophysics (AREA)
  • Biotechnology (AREA)
  • General Health & Medical Sciences (AREA)
  • Theoretical Computer Science (AREA)
  • Evolutionary Biology (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Molecular Biology (AREA)
  • Chemical & Material Sciences (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Analytical Chemistry (AREA)
  • Genetics & Genomics (AREA)
  • Organic Chemistry (AREA)
  • Physiology (AREA)
  • Wood Science & Technology (AREA)
  • Zoology (AREA)
  • Signal Processing (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Public Health (AREA)
  • Bioethics (AREA)
  • Evolutionary Computation (AREA)
  • Epidemiology (AREA)
  • Databases & Information Systems (AREA)
  • Artificial Intelligence (AREA)
  • Software Systems (AREA)
  • Data Mining & Analysis (AREA)
  • Microbiology (AREA)
  • Immunology (AREA)
  • Biochemistry (AREA)
  • General Engineering & Computer Science (AREA)
  • Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
  • Apparatus Associated With Microorganisms And Enzymes (AREA)

Abstract

A method for nucleic acid sequencing includes receiving observed or measured nucleic acid sequencing data from a sequencing instrument that receives and processes a sample nucleic acid in a termination sequencing-by-synthesis process. The method also includes generating a set of candidate sequences of bases for the observed or measured nucleic acid sequencing data by determining a predicted signal for candidate sequences using a simulation framework. The simulation framework incorporates an estimated carry forward rate (CFR), an estimated incomplete extension rate (IER), an estimated droop rate (DR), an estimated reactivated molecules rate (RMR), and an estimated termination failure rate (TFR), the RMR being greater than or equal to zero and the TFR being lesser than one. The method also includes identifying, from the set of candidate sequences of bases, one candidate sequence leading to optimization of a solver function as corresponding to the sequence for the sample nucleic acid.

Description

Docket No. LT00861 PCT
METHODS AND SYSTEMS FOR MODELING PHASING EFFECTS IN SEQUENCING
USING TERMINATION CHEMISTRY
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application claims priority to U.S. Prov. Appl. No. 61/886,878, filed on October 4, 2013, which is hereby incorporated by reference in its entirety.
TECHNICAL FIELD
[0002] This application generally relates to methods, systems, and computer readable media for nucleic acid sequencing, and, more particularly, to methods, systems, and computer readable medium for modeling phasing effects in nucleic acid sequencing.
BACKGROUND
[0003] Nucleic acid sequencing, in which the order of nucleotides in a nucleic acid molecule is determined, has become ubiquitous in a wide variety of medical applications, such as biological research, genetic testing, and so forth. One type of sequencing utilized in such applications is sequencing-by- synthesis in which the order of nucleotides in a nucleic acid strand is determined by synthesizing a corresponding strand. While sequencing-by- synthesis is a high throughput method employed in many current platforms, there are several drawbacks associated with its use. For example, sequencing-by- synthesis platforms generate large volumes of sequencing data that must subsequently be processed to determine the order of the nucleotides in a given nucleic acid strand. Further, the sequencing data obtained via these methods may include a variety of errors, such as loss of phase synchrony (i.e., loss of synchronous synthesis of the identical templates), that hinder the ability to make accurate base calls. Accordingly, there exists a need for systems and methods that address these issues and enable more accurate and efficient handling of the large volumes of sequencing data obtained via the sequencing-by- synthesis platforms. Docket No. LT00861 PCT
SUMMARY
[0004] Exemplary embodiments of the present disclosure may solve one or more of the above- mentioned problems and/or may demonstrate one or more of the above-mentioned desirable features. Other features and/or advantages may become apparent from the description that follows.
[0005] In accordance with at least one exemplary embodiment, a method for nucleic acid sequencing includes receiving observed or measured nucleic acid sequencing data from a sequencing instrument configured to receive a sample nucleic acid and to process the sample nucleic acid in a termination sequencing-by- synthesis process. The method also includes generating a set of candidate sequences of bases for the observed or measured nucleic acid sequencing data by determining a predicted signal for candidate sequences using a simulation framework for simulating possible state transitions for active and inactive molecules present at a K-th base during an N-th nucleotide flow, where K and N denote indices associated with bases and nucleotide flows, respectively. The simulation framework for simulating the possible state transitions incorporates an estimated carry forward rate (CFR), an estimated incomplete extension rate (IER), an estimated droop rate (DR), an estimated reactivated molecules rate (RMR), and an estimated termination failure rate (TFR), the RMR being greater than or equal to zero and the TFR being lesser than one. The method further includes identifying, from the set of candidate sequences of bases, one candidate sequence leading to optimization of a solver function as corresponding to the sequence for the sample nucleic acid.
[0006] In accordance with at least one exemplary embodiment, a nucleic acid sequencing system includes a sequencing instrument configured to receive a sample nucleic acid, at least one nucleotide having a terminating group, a primer, and a polymerase, and to process the sample Docket No. LT00861 PCT nucleic acid in a termination sequencing-by- synthesis process to produce raw nucleic acid sequencing data. A processor is configured to receive the raw nucleic acid sequencing data and to generate a set of candidate sequences of bases for sample nucleic acid by determining a predicted signal for candidate sequences using a simulation framework for simulating possible state transitions for active and inactive molecules present at a K-th base during an N-th nucleotide flow, where K and N denote indices associated with bases and nucleotide flows, respectively. The simulation framework for simulating the possible state transitions incorporates an estimated carry forward rate (CFR), an estimated incomplete extension rate (IER), an estimated droop rate (DR), an estimated reactivated molecules rate (RMR), and an estimated termination failure rate (TFR), the RMR being at a value greater than or equal to zero and the TFR being at a value lesser than one.
[0007] In accordance with at least one exemplary embodiment, an apparatus includes a machine readable memory and a processor configured to execute machine -readable instructions, the instructions which when executed cause the apparatus to receive observed or measured nucleic acid sequencing data from a sequencing instrument configured to receive a sample nucleic acid and to process the sample nucleic acid in a termination sequencing-by-synthesis process; and generate a set of candidate sequences of bases for the observed or measured nucleic acid sequencing data by determining a predicted signal for candidate sequences using a simulation framework for simulating possible state transitions for active and inactive molecules present at a K-th base during an N-th nucleotide flow, where K and N denote indices associated with bases and nucleotide flows, respectively. The simulation framework for simulating the possible state transitions incorporates an estimated carry forward rate (CFR), an estimated incomplete extension rate (IER), an estimated droop rate (DR), an estimated reactivated molecules rate Docket No. LT00861 PCT
(RMR), and an estimated termination failure rate (TFR), where the RMR is greater than or equal to zero and the TFR is lesser than one.
[0008] Additional objects, features, and/or advantages will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the present disclosure and/or claims. At least some of these objects and advantages may be realized and attained by the elements and combinations particularly pointed out in the appended claims.
[0009] It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the claims; rather the claims should be entitled to their full breadth of scope, including equivalents.
BRIEF DESCRIPTION OF THE DRAWINGS
[0010] The present disclosure can be understood from the following detailed description, either alone or together with the accompanying drawings. The drawings are included to provide a further understanding of the present disclosure, and are incorporated in and constitute a part of this specification. The drawings illustrate one or more exemplary embodiments of the present teachings and together with the description serve to explain certain principles and operation.
[0011] FIG. 1 is a schematic illustrating a sequencing-by- synthesis system, according to an embodiment of the present disclosure.
[0012] FIG. 2 is a flow chart illustrating a method for identifying a nucleic acid sequence, according to an embodiment of the present disclosure.
[0013] FIG. 3 is a schematic illustration of a simulation framework for calculating predicted ionograms, according to an embodiment of the present disclosure. Docket No. LT00861 PCT
[0014] FIG. 4 illustrates an example cell within the simulation framework of FIG. 3 along with possible states and state transitions, according to an embodiment of the present disclosure.
[0015] FIG. 5 illustrates an example cell within the simulation framework of FIG. 3 along with possible states and state transitions, according to another embodiment of the present disclosure.
[0016] FIG. 6 illustrates a simplified schematic illustration of a simulation framework for calculating predicted ionograms, according to an embodiment of the present disclosure;
[0017] FIG. 7 illustrates an example cell within the simulation framework of FIG. 6 along with possible states and state transitions, according to an embodiment of the present disclosure.
[0018] FIG. 8 illustrates a simplified schematic illustration of a simulation framework for calculating predicted ionograms, according to an embodiment of the present disclosure.
[0019] FIG. 9 illustrates an example cell within the simulation framework of FIG. 8 along with possible states and state transitions, according to an embodiment of the present disclosure.
[0020] FIGS. 10A-10D illustrate a simulated comparison of standard phasing and terminator phasing for a low noise level, according to an embodiment of the present disclosure.
[0021] FIGS. 11A-11D illustrate a simulated comparison of standard phasing and terminator phasing for a medium noise level, according to an embodiment of the present disclosure.
[0022] FIGS. 12A-12D illustrate a simulated comparison of standard phasing and terminator phasing for a high noise level, according to an embodiment of the present disclosure.
[0023] FIGS. 13A-13H illustrate simulated results for an incomplete extension rate of 0.5% in a termination chemistry sequencing-by- synthesis process, according to an embodiment of the present disclosure. Docket No. LT00861 PCT
[0024] FIGS. 14A-14H illustrate simulated results for an incomplete extension rate of 1.5% in a termination chemistry sequencing-by- synthesis process, according to an embodiment of the present disclosure.
[0025] FIGS. 15A-15H illustrate simulated results for an incomplete extension rate of 2.5% in a termination chemistry sequencing-by- synthesis process, according to an embodiment of the present disclosure.
[0026] FIGS. 16A-16H illustrate simulated results for an incomplete extension rate of 3.5% in a termination chemistry sequencing-by- synthesis process, according to an embodiment of the present disclosure.
[0027] FIGS. 17A-17H illustrate simulated results for an incomplete extension rate of 4.5% in a termination chemistry sequencing-by- synthesis process, according to an embodiment of the present disclosure.
DETAILED DESCRIPTION
[0028] This description and the accompanying drawings that illustrate exemplary embodiments should not be taken as limiting. Various mechanical, compositional, structural, electrical, and operational changes may be made without departing from the scope of this description and claims, including equivalents. In some instances, well-known structures and techniques have not been shown or described in detail so as not to obscure the disclosure. Like numbers in two or more figures represent the same or similar elements. Furthermore, elements and their associated features that are described in detail with reference to one embodiment may, whenever practical, be included in other embodiments in which they are not specifically shown or described. For example, if an element is described in detail with reference to one embodiment and is not Docket No. LT00861 PCT described with reference to a second embodiment, the element may nevertheless be claimed as included in the second embodiment.
[0029] For the purposes of this specification and appended claims, unless otherwise indicated, all numbers expressing quantities, percentages, or proportions, and other numerical values used in the specification and claims, are to be understood as being modified in all instances by the term "about," to the extent they are not already so modified. Accordingly, unless indicated to the contrary, the numerical parameters set forth in the following specification and attached claims are approximations that may vary depending upon the desired properties sought to be obtained. At the very least, and not as an attempt to limit the application of the doctrine of equivalents to the scope of the claims, each numerical parameter should at least be construed in light of the number of reported significant digits and by applying ordinary rounding techniques.
[0030] It is noted that, as used in this specification and the appended claims, the singular forms "a," "an," and "the," and any singular use of any word, include plural referents unless expressly and unequivocally limited to one referent. As used herein, the term "include" and its
grammatical variants are intended to be non-limiting, such that recitation of items in a list is not to the exclusion of other like items that can be substituted or added to the listed items.
[0031] In accordance with various exemplary embodiments, the present disclosure contemplates systems, methods, and computer readable media for evaluating sample nucleic acid sequences, including making base calls by processing and/or analyzing nucleic acid sequencing data that may be tainted by the presence of phasing effects capable of causing sequencing errors in a sequencing-by- synthesis process that utilizes termination chemistry. For example, in some embodiments, a solution to the sequencing problem of identifying the sequence of bases in a nucleic acid sample may be found by minimizing a distance (e.g. , through a least squares fit Docket No. LT00861 PCT framework) between a predicted set of values calculated under a phasing model and a measured set of values obtained via experimentation, for example, using a sequencing instrument. In some embodiments, the solution to the minimization problem may be identified by searching or traversing possible sequences with a tree -based solver. In this way, various exemplary embodiments of the present disclosure may enable base calls to be made by taking into account one or more phasing effects without the need to remove or correct for such phasing effects.
[0032] In various exemplary embodiments, the one or more phasing effects arising in the termination sequencing-by- synthesis process are captured as parameters that are estimated and provided as inputs to the phasing model. The parameters may be chosen to account for a variety of phasing errors that occur due to asynchronous synthesis among identical templates of the nucleic acid molecule to be sequenced. For example, the phasing model may incorporate parameters for incomplete extension, carry forward, droop, reactivated molecules, termination failure, and/or inactivated molecules. In this way, various exemplary embodiments may reduce or eliminate the likelihood that incorrect bases are called due to one or more phasing effects present in a termination chemistry sequencing-by-synthesis process. These and other features of various exemplary embodiments are discussed in more detail below with reference to the drawings.
[0033] FIG. 1 illustrates a nucleic acid sequencing system 10 capable of determining an order of nucleotides present in a nucleic acid sample. Polynucleotides may include the natural deoxyribonucleosides (e.g., deoxyadenosine, deoxycytidine, deoxyguanosine, and
deoxythymidine for DNA or their ribose counterparts for RNA) linked by phosphodiester linkages. However, they may also include non-natural nucleotide analogs, e.g., including modified bases, sugars, or internucleosidic linkages. In an exemplary embodiment, a Docket No. LT00861 PCT polynucleotide may be represented by a sequence of letters (upper or lower case), such as "ATGCCTG," and it will be understood that the nucleotides are in 5'→3' order from left to right and that "A" denotes deoxyadenosine, "C" denotes deoxycytidine, "G" denotes deoxyguanosine, and "T" denotes deoxythymidine, and that "I" denotes deoxyinosine, and "U" denotes deoxyuridine, unless otherwise indicated or obvious from context.
[0034] The nucleic acid sequencing system 10 includes a control and processing system 12 that receives nucleic acid sequencing data from a sequencing instrument 14 for analysis and/or processing. The sequencing instrument 14 is configured to perform a sequencing-by-synthesis process using termination chemistry ("termination sequencing-by- synthesis"). As used herein, the term "termination sequencing-by- synthesis" encompasses all sequencing-by- synthesis processes that employ any type of termination chemistry. For example, termination sequencing- by-synthesis includes, but is not limited to, sequencing-by- synthesis processes in which nucleic acid replication is reversibly or irreversibly terminated in a stepwise fashion via incorporation of one or more terminators, such as chemically altered dNTPs (e.g. , chemically altered dATP, dCTP, dGTP, and/or dTTP), including 2*,3* dideoxynucleotides (ddNTPs) (e.g. , ddATP, ddCTP, ddGTP, ddTTP) into the reaction mixture.
[0035] One or more materials 16 are provided in various concentrations under control of flow controller 18. In the illustrated embodiment, the materials include nucleic acid polymerase 20, nucleic acid primer 22, nucleic acid template 24, deoxyrobonucleotides (dNTP(s)) (e.g. , dATP, dCTP, dGTP, dTTP) 26, and 2*,3* dideoxynucleotides (ddNTPs) (e.g. , ddATP, ddCTP, ddGTP, ddTTP) 28, although as discussed in detail below, the materials 16 provided for a given application may vary, for example, depending on implementation- specific considerations. Docket No. LT00861 PCT
[0036] The illustrated embodiment of the control and processing system 12 includes an internal bus 30 to which a processor 32 is connected to enable communication with a variety of other system components. Control and processing system 12 also includes a random access memory (RAM), or other dynamic memory, coupled to bus 30 for storing instructions to be executed by the processor 32. The RAM 34 may also be used for storing temporary variables or other intermediate information during execution of instructions to be executed by the processor 32. Further, a read only memory (ROM) 36, or other static storage device, is provided for storing static information and instructions for the processor 32. The control and processing system 12 may also include a storage device 38, such as a magnetic disk, optical disk, or solid state drive (SSD) for storing information or instructions. The storage device 38 may include a media drive and a removable storage interface. A media drive may include a drive or other mechanism to support fixed or removable storage media, such as a hard disk drive, a floppy disk drive, a magnetic tape drive, an optical disk drive, a CD or DVD drive (R or RW), flash drive, or other removable or fixed media drive. The storage device 38 may further include a computer-readable storage medium having stored therein particular computer software, instructions, or data.
[0037] The control and processing system 12 may also include a communications interface 40 that enables software and/or data to be transferred between computing system the control and processing system 12 and one or more external devices. Examples of communications interface 40 include a modem, a network interface (such as an Ethernet or other NIC card), a
communications port (such as for example, a USB port, a RS-232C serial port), a PCMCIA slot and card, Bluetooth, and the like. Software and data transferred via the communications interface 40 may be in the form of signals, which can be electronic, electromagnetic, optical or other signals capable of being received by communications interface 40. These signals may be Docket No. LT00861 PCT transmitted and received by communications interface 40 via a channel, such as a wireless medium, wire or cable, fiber optics, or other communications medium.
[0038] One or more control inputs 42 may be communicated to the processor 32 via the communications interface 40. Control inputs 42 may be provided via one or more input devices, such as a keyboard, an interactive display, such as an LCD display configured with touch screen input capabilities, a cursor control, such as a mouse, and so forth. Further, the processor 32 may also be coupled via bus 30 to a display 44, such as a cathode ray tube (CRT) or liquid crystal display (LCD), for displaying information to a user.
[0039] During operation of the nucleic acid sequencing system, the sequencing instrument 14 performs a termination sequencing-by-synthesis process, thereby generating raw data
corresponding to an incorporation signal indicative of one or more nucleotide incorporations into a nucleic acid strand being synthesized in the sequencing operation. Further, in the illustrated nucleic acid sequencing system 10, as mentioned above, nucleic acid polymerase 20, nucleic acid primer 22, a nucleic acid template 24 to be sequenced, dNTP(s) 26, and ddNTP(s) 28 are provided as inputs to the sequencing instrument 14 for use in the termination sequencing-by- synthesis process. However, as understood by those of ordinary skill in the art, the particular type, mixture, and timing of the reactants provided to the sequencing instrument 14 will vary depending on a variety of implementation- specific considerations, such as the type of sequencing-by-synthesis method being employed, the type of termination chemistry used, the available imaging or sensing platforms, and so forth. Accordingly, the materials 16 shown in FIG. 1 are non-limiting examples of the types of reactants that could be provided to the sequencing instrument. Docket No. LT00861 PCT
[0040] In various exemplary embodiments, the terminator provided to the sequencing instrument 14 may include any of a variety of classes of terminators suitable for terminating primer extension. For example, suitable terminators include irreversible terminators, such as ddNTPs that lack a 3' hydroxyl and, thus, interrupt nucleic replication by virtue of a hydrogen instead of a hydroxyl at the 3' position. As an additional example, reversible terminators also may be utilized. Such terminators may include 3'-0-blocked reversible terminators and 3 '-unblocked reversible terminators. Suitable 3'-0-blocked reversible terminators may include a terminating group linked to the oxygen atom of the 3' hydroxyl of the pentose. Several commercially available terminators of this type may be utilized in different implementations, including but not limited to 3'-ONH2 reversible terminators, 3'-0-allyl reversible terminators, and 3'-0- azidomethy reversible terminators. Suitable 3 '-unblocked reversible terminators include an intact 3' hydroxyl group and a terminating group linked to the base for termination of primer extension. Several commercially available terminators of this type may be utilized in different implementations, including but not limited to the 3' -OH unblocked reversible terminator named "virtual terminator" and the 3' -OH unblocked nucleotides termed "Lightening Terminators™," which have a terminating 2-nitrobenzyl moiety attached to hydroxymethylated nucleobases.
[0041] Depending on the type of terminator selected, the particular polymerase 20 selected for use in the processes performed by the sequencing instrument 14 may vary. That is, the type of nucleotide analog selected for the nucleic acid sequencing may impact the type of DNA polymerase 20 that will yield the optimal efficiency. For example, in one embodiment, the Lightening Terminators™ may be selected for use as the terminator, and the Therminator™ DNA polymerase developed for use with the Lightening Terminators™ may be utilized to optimize efficiency. Docket No. LT00861 PCT
[0042] Further, depending on the type of the selected sequencing-by-synthesis process and the type of termination chemistry employed, the order and mixture of the dNTPs 26 and/or the ddNTPs 28 may be varied by the flow controller 18. For example, if a Sanger sequencing process is selected to be run by the sequencing instrument 14, four separate sequencing reactions may be run, each including one of the four types of ddNTPs and the other three dNTPs (e.g. , one reaction would include ddATP, but dGTP, dCTP, and dTTP). For further example, if a dye termination sequencing process is selected to be employed by the sequencing instrument 14, the flow controller 18 may regulate a reaction including all four of the ddNTPs 28 (i.e. , ddATP, ddCTP, ddGTP, ddTTP), each coupled to a different color fluorescent marker to enable identification, for example, via a fluorescent based imaging system.
[0043] According to one exemplary embodiment, the sequencing instrument 14 may be configured to perform electronic or charged-based nucleic acid termination sequencing-by- synthesis. In such an embodiment utilizing electronic or charged-based sequencing (e.g. , pH- based sequencing) employing termination chemistry, an incorporation signal generated from a nucleotide incorporation event may be determined by detecting ions (e.g. , hydrogen ions) that are generated as natural by-products of polymerase-catalyzed nucleotide extension reactions. This may be used to sequence a sample or template nucleic acid, which may be a fragment of a nucleic acid sequence of interest, for example, and which may be directly or indirectly attached as a clonal population to a solid support, such as a particle, microparticle, bead, etc. The sample or template nucleic acid 24 may be operably associated to a primer 22 and polymerase 20. The template nucleic acid 24 may be subjected to repeated cycles or "flows" (which may be referred to herein as "nucleotide flows" from which nucleotide incorporations may result with
corresponding generation of incorporation signals) of terminators and washes. In one Docket No. LT00861 PCT embodiment, the terminator utilized may be one of the Lightening Terminators™, and the polymerase may be one of the Therminator™ DNA polymerase, such as Therminator III.
[0044] The primer 22 may be annealed to the sample or template 24 so that the primer's 3' end can be extended by a polymerase whenever, for example, ddNTPs 28 complementary to the next base in the template are added. Then, based on the known sequence of nucleotide flows and on measured incorporation signals during each nucleotide flow, the identity of the type, sequence and number of nucleotide(s) associated with a sample nucleic acid 24 present in a reaction chamber can be determined.
[0045] The sequence of nucleotide flows may be based on a cyclical, repeating pattern consisting of consecutive repeats of a short pre-determined cycle of nucleotide flows (e.g., consecutive repeats of pre-determined sequence of four nucleotide flows such as, for example, "ACTG ACTG. . ."); may be based in whole or in part on some other pattern of nucleotide flows (such as, e.g., any of the various nucleotide flow orders discussed or contemplated in Hubbell et al., U.S. Pat. Appl. Publ. No. 2012/0264621, published October 18, 2012); or may also be based on some combination thereof.
[0046] In one embodiment, the four different kinds of ddNTPs are added sequentially to the reaction chambers, so that each reaction is exposed to the four different ddNTPs, one at a time. In an exemplary embodiment, the four different kinds of ddNTPs are added in the following sequence: ddATP, ddCTP, ddGTP, ddTTP, ddATP, ddCTP, ddGTP, ddTTP, etc., with each exposure followed by a wash step. Each exposure to a ddNTP followed by a washing step can be considered a "nucleotide flow." Four consecutive nucleotide flows can be considered a "cycle." For example, a two cycle nucleotide flow order can be represented by: ddATP, ddCTP, ddGTP, ddTTP, ddATP, ddCTP, ddGTP, ddTTP, with each exposure being followed by a wash Docket No. LT00861 PCT step. In certain embodiments employing termination chemistry utilizing one or more of the terminators discussed above, each nucleotide flow may lead to a single nucleotide incorporation before primer extension is terminated.
[0047] FIG. 2 illustrates an embodiment of a method 50 for identifying a nucleic acid sequence of a DNA template. The method 50 includes receiving raw data in the form of measured or observed data obtained via a sequencing operation (block 52). For example, raw data may be received by the processor 32 of the control and processing system 12 from the sequencing instrument 14 after running a termination sequencing-by-synthesis process. The processor 32 may include a solver configured to transform the raw data received at block 52 into a base call and compile consecutive base calls associated with a sample nucleic acid template into a read, with each base call referring to a particular nucleotide identification (e.g. , dATP ("A"), dCTP ("C"), dGTP ("G"), dTTP ('?')).
[0048] In order to transform this raw data into base calls, a phasing model may be generated to model the phasing effects that can occur in the termination sequencing-by- synthesis process and enable such phasing effects to be taken into account when processing or analyzing the raw data to determine the base calls. To that end, in the illustrated embodiment, an estimate of one or more of six parameters may be estimated at blocks 54, 56, 58, 60, 62, and 64. Specifically, the method 50 can include obtaining an estimate for a carry forward rate (CFR) (block 54). The CFR may be a parameter that encompasses plus frame shifts and corresponds to the rate at which nucleic acid copies incorporate a nucleotide different from the one flown in a given flow cycle.
[0049] The method 50 also can include obtaining an estimate of an incomplete extension rate (IER) (block 56). The IER may be a parameter that encompasses minus frame shifts and corresponds to the rate at which nucleic acid copies fail to extend during a flow cycle. The Docket No. LT00861 PCT method 50 further can include obtaining an estimate of a droop rate (DR) (block 58), which corresponds to a rate at which active nucleic acid copies become inactive during a cycle. The transition from active to inactive may occur, for example, due to incomplete removal of a terminating group or polymerase inactivation.
[0050] Still further, the method 50 can include obtaining an estimate for a reactivated molecules rate (RMR) (block 60). The RMR corresponds to the rate at which inactive nucleic acid copies become reactivated at a later point in time than intended. This parameter may encompass instances in which a terminating group was previously left intact and removed at a later time. Additionally, the method 50 can include obtaining an estimate for a termination failure rate (TFR) (block 62). The TFR corresponds to the rate at which phasing errors occur due to ineffective termination of primer extension. For example, in embodiments employing a 3'- unblocked reversible terminator, the TFR may include the rate at which the terminating group fails to prevent the polymerase from recognizing the 3' hydroxyl group and an additional nucleotide is therefore incorporated. The TFR may also include the rate at which the other types of terminators described in detail above fail to terminate primer extension and the rate at which a given polymerase fails to discriminate the terminating group at the 3' location, thus incorporating additional nucleotides.
[0051] In addition, the method 50 can include obtaining an estimate for inactivated molecules rate (IMR) (block 64). The IMR corresponds to the rate at which nucleic acid copies become inactive after they have incorporated a base and after the corresponding incorporation signal has been detected. Such inactivation may occur, for example, due to the use of irreversible terminators or due to a general failure of reverse termination when reversible terminators are used. Docket No. LT00861 PCT
[0052] Once the estimates are obtained for the six identified parameters, or a subset of one or more of the six parameters being employed depending on the implementation, the method 50 includes generating a set of candidate sequences by simulating possible molecule state transitions for active and inactive molecules at each flow and base (block 66) and identifying which sequence of the generated set of sequences optimizes a solver function (block 68).
[0053] For example, in one embodiment, a solver may be configured as a software tool or application with functionality to efficiently solve or determine, from a set of possible or candidate sequences of bases, which sequence is in some sense most consistent with some observed or measured raw data. Possible or candidate sequences may be evaluated by predicting data that would be expected for such sequences under one or more predictive models
incorporating the estimated parameters and determining how "close" under some distance criterion the predicted data are from the observed data.
[0054] To illustrate this, let Y represent observed or measured data (e.g., a vector of values such as an observed or measured ionogram or flowgram, for example, or other sequencing values), let X represent predicted data (e.g., a vector of values such as a predicted ionogram or flowgram), let A represent a set of possible or candidate nucleic acid or base sequences (e.g., the set comprising the possible sequences of A, C, G, and T; the set comprising the possible sequences of A, C, G, and T that have at most a certain length; or any other subset of candidate sequences), and let P represent a set of parameters used by the one or more predictive models (e.g., one or more of the parameters for the incomplete extension, carry-forward, droop, reactivated molecules, termination failure rates, inactivation rates). Then, in an embodiment, the solver may be thought of as a function / that determines for some defined space or reaction confinement Docket No. LT00861 PCT regions comprising one or more sample nucleic acids a "best" candidate sequence A* from set A such that
A* = f{Y, X(A, P)) gAiP mm D (Y - X(A, where min f (x, y) generally denotes the value (or values) of x and y that would generally minimize the function /(x,y) and where D(y-x) denotes some function of the "distance" between y and x (e.g., a sum of squared distances or any other measure of a distance between vectors, for example).
[0055] Such a solver may in principle consider the possible combinations of sequences in set A and values for the parameters in set P to identify an optimal combination of a sequence and parameter values. Of course, such an exhaustive search may be computationally expensive and potentially very time consuming. In practice, the search may advantageously be limited to a subset of sequences and subset of candidate values for the parameters. In an embodiment, the search may be facilitated by performing parameter estimation (e.g. , as in blocks 54, 56, 58, 60, 62, and 64 of FIG. 2) separately from the optimization, dividing the process into two phases. For example, in a first step, the parameters may be estimated, and in a second step, the parameter estimates may be treated as fixed and supplied as inputs to the solver problem, which could then be reformulated as
A* = f(Y, X, A, P) = argA mm D (Y - X(A \P)), where X(AIP) denotes X as a function of A given some fixed parameters P. Docket No. LT00861 PCT
[0056] In one embodiment, for example with P including the first five parameters (e.g., incomplete extension, carry-forward, droop, reactivated molecules, and termination failure rates represented as IER, CFR, DR, RMR, and TFR, respectively), then an optimal sequence A* may be found as follows: First, estimates of IER, CFR, DR, RMR, and TFR may be obtained using any suitable method. Reference is made to Davey et al., U.S. Patent No. 8,666,678, filed Oct. 27, 2011, and in Davey et al., U.S. Publication No. 2014/0051584, filed Aug. 15, 2013, which are all incorporated by reference herein in their entirety, and which disclose exemplary techniques for estimating IER, CFR, and DR, with those of ordinary skill in the art understanding how such techniques may be applied to provide additional parameter estimations, for example, by using the disclosed techniques to also estimate RMR, TFR, and/or EVIR. Further, in some embodiments, one or more of the parameters may be estimated separately for each cell in a dynamic programming matrix (e.g., for each cell in matrix 70, 120, and/or 130 described below), thereby resulting in variations in the estimated parameters across cells of a given matrix. In another embodiment, one or more of the parameters may be set at a fixed estimation value for a given row in the dynamic programming matrix while one or more of the remaining parameters in different columns of the matrix vary from cell to cell. Indeed, the parameter estimations for each of the cells of a matrix may vary in a variety of suitable manners, depending on the given implementation.
[0057] Second, A* may be found by solving
A* = argA min D (Y— X(A \ IER, CFR, DR, RMR, TFR) ), where X(AIP) denotes X as a function of A given some fixed parameters P (e.g., IER, CFR, DR, RMR, and TFR in this example). Any suitable optimization method may be used to solve this Docket No. LT00861 PCT problem, such as using a tree-based solver. Also, it should be noted that the foregoing approach can be applied using a different number or combination of the six parameters described above and the five above should be understood to be one non-limiting exemplary illustration.
[0058] Indeed, in some embodiments, a subset of the six disclosed parameters may be utilized. For instance, in one embodiment, three parameters, IER, CFR, and DR may be utilized with a termination sequencing-by-synthesis process. In another embodiment, four parameters may be utilized, for example, combining IER, CFR, DR, and RMR with TFR set to zero, or combining IER, CFR, DR, and TFR, with RMR set to zero. However, in other embodiments, the preceding five parameters may be incorporated into the model with RMR and TFR both set at values greater than zero, but with TMR less than 1. Yet another embodiment in which irreversible terminators are utilized may incorporate all of the six disclosed parameters, including IER, CFR, DR, TFR, RMR, and IMR. Indeed, the possible permutations of the parameter models provided herein enables the phasing models according to various exemplary embodiments to be applicable across a variety of sequencing platforms, including platforms that do not utilize termination chemistry. For example, in one embodiment in which termination chemistry is not employed, the five parameter model described above may collapse to a three parameter model by setting RMR to zero and TFR to one, as described in more detail below.
[0059] FIGS. 3-9 illustrate exemplary embodiments of simulation frameworks and matrices that can be utilized to calculate predicted ionograms. The particular simulation framework and matrix chosen for a given application may depend on a variety of implementation- specific considerations and factors, such as, for example, the type of termination chemistry being utilized in the sequencing-by-synthesis process. For example, FIGS. 3 and 4 illustrate a simulation framework and matrix, respectively, which may be utilized to calculate predicted ionograms in a Docket No. LT00861 PCT termination sequencing-by-synthesis process utilizing, for example, reversible terminators as disclosed above. For further example, FIGS. 3 and 5 illustrate a simulation framework and matrix, respectively, which may be utilized to calculate predicted ionograms in a termination sequencing-by-synthesis process utilizing, for example, irreversible terminators as disclosed above.
[0060] More specifically, FIG. 3 illustrates schematically a simulation framework 70 for calculating predicted ionograms, according to an embodiment of the present invention. The representation includes various steps and can be thought of as a matrix of the nucleotide flows (e.g. , columns representing flows 1, 2, 3, and so on) and nucleotide bases (e.g. , rows representing bases 1, 2, 3, and so on). Bases may or may not incorporate during a particular intended flow, and moreover may incorporate during unintended flows, as described in further detail below. Simulations of intended incorporations, incorporation failures, and/or unintended incorporations generate paths along the cells of such a matrix.
Five Parameter Phasing Model
[0061] FIG. 4 illustrates an exemplary cell 80 within the matrix illustrated in FIG. 3, with possible molecule states and state transitions labeled, according to one disclosed embodiment. Such a cell illustrates what may happen for active molecules (e.g. , a molecule being actively synthesized during a flow with an active polymerase) and inactive molecules present at the K-th base during the N-th nucleotide flow in parameter phasing model incorporating the five parameters, IER, CFR, DR, RMR, and TFR. Such a phasing model may be useful in a termination sequencing-by-synthesis platform that uses reversible terminators, for example. To arrive at this point, active molecules include those that either incorporated base K-1 in flow N or Docket No. LT00861 PCT did not incorporate base K in flow N-1. Inactive molecules include molecules that incorporated K-l bases in N-1 flows.
[0062] For the active molecules that incorporated base K- l in flow N (labeled as Qi in FIG. 4), there are then two possibilities at juncture 82. Either the terminating group failed to terminate the primer extension (e.g. , Qi', which equals QiX[TFR]) or the termination was reversed (e.g. , Qi", which equals Qi - Qi' or Qi x[l-TFR]). As will be discussed further below, the Qi' subset are passed to juncture 86 where they may then undergo one of three possibilities within cell 80 (i.e., at the Kth base for flow N), and the Qi" subset is passed to juncture 89. The active molecules that enter cell 80 due to a failure to incorporate base K in the N- 1 flow is represented by Q2 in FIG. 4, and this subset of active molecules also is passed to juncture 86 in FIG. 4.
[0063] For the inactive molecules having incorporated K- l bases in N- 1 flows that enter cell 80 (labeled Q6), those inactive molecules may either become reactivated (Q6') or remain inactive (Q6") at juncture 84. As with the other active molecules, the subset Q6' is passed to juncture 86.
[0064] Thus, arriving at juncture 86 is the sum of the active molecules (Qi' , Q2, and Q6') in cell 80. At juncture 86, one of three possibilities can occur. The active molecules may fail to extend or undergo incomplete extension, which subset Q8 is passed to juncture 89; they may become inactive and undergo droop, which subset Q5 is passed to juncture 90; or they may undergo normal extension or a carry forward event and incorporate base K in flow N, which subset of molecules Q4 becomes active molecules that have incorporated base K in flow N and move to the next cell along a flow column N.
Five Parameter Phasing Model - K-th Base Matches N-th Flow Docket No. LT00861 PCT
[0065] Referring to the exemplary cell 80 within a matrix as illustrated in FIG. 4, in situations where the K-th base matches the N-th flow, the various transitions at the various junctures may be as follows: juncture 82 has one input (Qi) and two outputs (Qi' = Qi x [TFR] and Qi" = Qi x [1- TFR]); juncture 84 has one input (Q6) and two outputs (Q6' = Q6 [RMR] and Q6" = Q6 x [1 - RMR]; juncture 86 has three inputs (Qi', Q2, and Q6') and three outputs (Q8 = (Qi' + Q2 + Q6') x [IER x (1 - DR)], Q5 = (Qi' + Q2 + Q6') x [DR], and Q4 = (Qi' + Q2 + Q6') x ([1 - IER] x [1 - DR])); juncture 89 has two inputs (Qi" and Q8) and one output (Q3 = Qi" + Q8); and juncture 90 has two inputs (Q5 and Q6") and one output (Q7 = Q5 + Q6")- Therefore, with respect to the outputs from the exemplary cell 80 (Q3, Q4, and Q7), Q3 may be determined directly or indirectly from prior states based on four transition factors that are based on four of the five parameters. Those transition factors are [TFR], [1- TFR], [RMR], and [IER x (1 - DR)], respectively. Q4 may be determined directly or indirectly from prior states based on three transition factors ([TFR], [RMR], and ([1 - IER] x [1 - DR])). Q7 may be determined directly or indirectly from prior states based on four transition factors ([TFR], [RMR], (1 - [RMR]), and [DR]).
[0066] The proportion of molecules that will remain active and not incorporate base K in flow N (Q3) may be determined by multiplying some measure of the quantity (e.g., number,
concentration, etc.) of molecules in the prior active states by the corresponding transition factors and adding the resulting quantities (e.g., multiplying (Qi'+Q2+Q6' ) by a transition factor
[IERx(l-DR)] to obtain Q8 and multiplying Qi by a transition factor [1-TFR] to obtain Qi", and adding Q8 and Qi" to obtain Q3). Conversely, the proportion of molecules that will remain active and incorporate base K in flow N (Q4) may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the active prior states by the Docket No. LT00861 PCT corresponding transition factor (e.g., multiplying (Qi '+(¾+(¾' ) by a transition factor
[(l-IER)x(l-DR)] to obtain Q4).
[0067] Further, the proportion of molecules that will be inactive having incorporated K- 1 bases in N flows (Q7) may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the prior active or inactive states reaching the transition by the corresponding transition factors and adding the resulting quantities (e.g., multiplying
(Q1 +Q2+Q6 ) by a transition factor [DR] to obtain Q5 and multiplying Q6 by a transition factor [1-RMR] to obtain Q6", and adding Q5 and Q6" to obtain Q7) .
Five Parameter Phasing Model - K-th Base Does Not Match N-th Flow
[0068] In situations where the K-th base does not match the N-th flow, the various transitions at the various junctures in FIG. 4 may be as follows: juncture 82 has one input (Q and two outputs (Qj' = Qi x [TFR] and Qf = Qi x [1- TFR]); juncture 86 has three inputs (Qf , Q2, and Q6') and three outputs (Q8 = (Qf + Q2 + Q6') x [(1 - CFRM) + CFRM x IER x (1 - DR)], Q5 = (Qi' + Q2 + Q6') x [CFRM x DR], and Q4 = (Qf + Q2 + Q6') x (CFRM x [1 - IER] x [1 - DR])); juncture 89 has two inputs (Qi" and Qg) and one output (Q3 = Qf + Qg); juncture 84 has one input (Q6) and two outputs (Q6' = Q6 [RMR] and Q6" = Q6 x [1 - RMR]; and juncture 90 has two inputs (Q5 and Q6") and one output (Q7 = Q5 + where M is the smallest number such that the (N-M)- th flow matches the K-th base. Therefore, with respect to the outputs from the exemplary cell 80 when the K-th base does not mat the N-th flow, Q3 may be determined directly or indirectly from prior states based on four transition factors that are based on the five parameters. Those factors are [TFR], [1- TFR], [RMR], and [(1 - CFRM) + CFRM x IER x (1 - DR)])]. Q4 may be determined directly or indirectly from prior states based on three transition factors ([TFR], Docket No. LT00861 PCT
[RMR], and (CFRM x [1 - IER] x [1 - DR])), and Q7 may be determined directly or indirectly from prior states based on four transition factors ([TFR], [RMR], (1 - [RMR]), and [CFRM x DR]).
[0069] For the case where the K-th based does not match the N-th flow, the proportion of molecules that will remain active and not incorporate base K in flow N (e.g., Q3) may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the prior active states by the corresponding transition factors and adding the resulting quantities (e.g., multiplying (Qi'+C +Qe') by a transition factor comprising term
[(l-CFRM)+(CFRMxIERx(l-DR))], where M is the smallest number such that the (N-M)-th flow matches the K-th base, to obtain Q8 and multiplying Qi by a transition factor [1-TFR] to obtain Qi", and adding Q8 and Qi" to obtain Q3). Conversely, the proportion of molecules that will remain active and incorporate base K in flow N (Q4) may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the active prior states by the corresponding transition factor (e.g., multiplying (Qi'+Q2+Q6') by a transition factor comprising term [CFRMx(l-IER)x(l-DR)] to obtain Q4). Further, the proportion of molecules that will be inactive having incorporated K-l bases in N flows (Q7) may be determined by combining the quantities (e.g., number, concentration, etc.) of molecules in the prior states by the corresponding transition factors and adding the resulting quantities (e.g., multiplying (Qi'+Q2+Q6') by a transition factor [CFRMxDR] to obtain Q5 and multiplying Q6 by a transition factor [1-RMR] to obtain Q6", and adding Q5 and Q6" to obtain Q7). Docket No. LT00861 PCT
Six Parameter Phasing Model
[0070] FIG. 5 illustrates an exemplary cell 110 within the matrix illustrated in FIG. 3, with possible molecule states and state transitions labeled, according to another exemplary in which a sixth parameter is incorporated into the phasing model described in detail above. This additional parameter is an inactivated molecules rate (IMR) and corresponds to the rate at which the molecules are inactivated, which may be useful in an implementation that uses irreversible terminators or when the reversal process of reversible terminators is imperfect.
[0071] The exemplary cell 110 illustrates what may happen for active molecules (e.g. , a molecule being actively synthesized during a flow with an active polymerase) and inactive molecules present at the K-th base during the N-th nucleotide flow in the six parameter model incorporating the IMR. To arrive at this point, active molecules include those that either incorporated base K-l in flow N or did not incorporate base K in flow N-1. Inactive molecules include molecules that incorporated K- l bases in N- 1 flows.
[0072] For the active molecules that incorporated base K- l in flow N (labeled as Qi in FIG. 5), there are then three possibilities at juncture 82. Either the terminating group failed to terminate the primer extension (e.g. , Qi ' , which equals Qi multiplied by the termination failure rate, or QiX[TFR], the molecules were inactivated (e.g. , Qi ' " , which equals QiX[IMR]), or the termination was reversed (e.g. , Qi " , which equals Qi - Qi ' -Qi ' " or Qi x[l-TFR-IMR]). As will be discussed further below, the Qi ' subset are passed to juncture 86, where they may then undergo one of three possibilities within cell 80 (i.e., at the Kth base for flow N), the Qi" subset is passed to juncture 89, and the Qi ' " subset is passed to juncture 84. The active molecules that enter cell 80 due to a failure to incorporate base K in the N-1 flow is represented by Q2 in FIG. 5, and this subset of active molecules also is passed to juncture 86 in FIG. 5. Docket No. LT00861 PCT
[0073] For the inactive molecules having incorporated K-l bases in N-l flows that enter cell 80 (Q6), those inactive molecules are combined with the inactivated molecules (Qi' ") at juncture 84, and the molecules at juncture 84 may then either become reactivated (Q6') or remain inactive (Q6"). As with the other active molecules, the subset Q6' is passed to juncture 86.
[0074] Thus, arriving at juncture 86 is the sum of the active molecules
Figure imgf000028_0001
Q2, and Q6') in cell 80. At juncture 86, one of three possibilities can occur. The active molecules may fail to extend or undergo incomplete extension, which subset Q8 is passed to juncture 89; they may become inactive and undergo droop, which subset Q5 is passed to juncture 90; or they may undergo normal extension or a carry forward event and incorporate base K in flow N, which subset of molecules Q4 becomes active molecules that have incorporated base K in flow N and move to the next cell along a flow column N.
Six Parameter Phasing Model - K-th Base Matches N-th Flow
[0075] Referring to the exemplary cell 110 within a matrix as illustrated in FIG. 5, in situations where the K-th base matches the N-th flow, the various transitions at the various junctures may be as follows: juncture 82 has one input (Qi) and three outputs (Qi' = Qi x [TFR]; Qi" = Qi x
[1- TFR-IMR], and Q'" = QiX[IMR] ); juncture 84 has two inputs (Qi' " and Q6) and two outputs (Q6' = (Q6+Qi'")x[RMR] and Q6" = (Q6+Qi'")x[l-RMR]); juncture 86 has three inputs (Qf , Q2, and Q6') and three outputs (Q8 = (Qi' + Q2 + Q6') x [IER x (1 - DR)], Q5 = (Qi' + Q2 + Qe') x [DR], and Q4 = (Qi' + Q2 + Q6') x ([1 - IER] x [1 - DR])); juncture 89 has two inputs (Qi" and Qg) and one output (Q3 = Qi" + Qs);; and juncture 90 has two inputs (Q5 and Q6") and one output (Q7 = Q5 + Qe"). Docket No. LT00861 PCT
[0076] Therefore, with respect to the outputs from the exemplary cell 110 (Q3, Q4, and Q7), Q3 may be determined directly or indirectly from prior states using five transition factors based on five of the six parameters, the five transition factors being [IMR], [TFR], [1- TFR-IMR], [RMR], and [IER x (1 - DR)]. Q4 may be determined directly or indirectly from prior states based on transition factors [IMR], [TFR], [RMR], and ([1 - IER] x [1 - DR]). Q7 may be determined directly or indirectly from prior states based on transition factors [IMR], [TFR], [RMR], (1 - [RMR]), and [DR].
[0077] The proportion of molecules that will remain active and not incorporate base K in flow N (Q3) may be determined by multiplying some measure of the quantity (e.g., number,
concentration, etc.) of molecules in the prior active states by the corresponding transition factors and adding the resulting quantities (e.g., multiplying (Qi'+C +Qe ) by a transition factor
[IERx(l-DR)] to obtain Q8 and multiplying Qx by a transition factor [1 -TFR-IMR] to obtain Qi", and adding Q8 and Qf to obtain Q3). Conversely, the proportion of molecules that will remain active and incorporate base K in flow N (Q4) may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the active prior states by the corresponding transition factor (e.g., multiplying (Qi'+C +Qe ) by a transition factor [(l-IER)x(l-DR)] to obtain Q4). Further, the proportion of molecules that will be inactive having incorporated K-1 bases in N flows (Q7) may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the prior active or inactive states reaching the transition by the corresponding transition factors and adding the resulting quantities (e.g., multiplying (Qi'+C +Qe ) by a transition factor [DR] to obtain Q5 and multiplying (Q6+Q1 ' " ) by a transition factor [1-RMR] to obtain Q6", and adding Q5 and Q6" to Docket No. LT00861 PCT obtain Q7) .
Six Parameter Phasing Model - K-th Base Does Not Match N-th Flow
[0078] Referring to the exemplary cell 110 within a matrix as illustrated in FIG. 5, in situations where the K-th base does not match the N-th flow, the various transitions at the various junctures may be as follows: juncture 82 has one input (Qi) and three outputs (Qi' = Qi x [TFR], Qi'" = Qi x [IMR] and Qi" = Qi x [1- TFR-IMR]); juncture 84 has two inputs (Qi' " and Q6) and two outputs (Q6' = (Q6+Qi'")x[RMR] and Q6" = (Q6+Qi'")x[l-RMR]); juncture 86 has three inputs (Qi', Q2, and Q6') and three outputs (Q8 = (Qi' + Q2 + Q6') [(1-CFRM) + CFRM x IER x (1 - DR)], Q5 = (Qi' + Q2 + Q6') x [CFRM x DR], and Q4 = (Qi' + Q2 + Q6') ([CFRM] x [1 - IER] x [1 - DR]); juncture 89 has two inputs (Qi" and Q8) and one output (Q3 = Qi" + Q8); and juncture 90 has two inputs (Q5 and Q6") and one output (Q7 = Q5 + Q6")- [0079] Therefore, with respect to the outputs from the exemplary cell 110 (Q3, Q4, and Q7), Q3 may be determined directly or indirectly from prior states using five transition factors based on the six parameters, the five transition factors being [IMR], [TFR], [1- TFR-IMR], [RMR], and [(1-CFRM) + (CFRM x IER x (1 - DR)]) Q4 may be determined directly or indirectly from prior states based on transition factors [IRR], [TFR], [RMR], and [CFRM x (1 - IER) x (1 - DR)], and Q7 may be determined directly or indirectly from prior states based on transition rates [IRR], [TFR], [RMR], [1 - RMR], and [CFRM x DR].
[0080] The proportion of molecules that will remain active and not incorporate base K in flow N (Q3) may be determined by multiplying some measure of the quantity (e.g., number,
concentration, etc.) of molecules in the prior active states by the corresponding transition factors and adding the resulting quantities (e.g., multiplying (Qi'+Q2+Q6') by a transition factor [(1- CFRM) + (CFRM x IERx(l-DR)] to obtain Q8 and multiplying Qi by a transition factor [1-TFR- Docket No. LT00861 PCT
IMR] to obtain Qi", and adding Q8 and Qf to obtain Q3). Conversely, the proportion of molecules that will remain active and incorporate base K in flow N (Q4) may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the active prior states by the corresponding transition factor (e.g., multiplying (Qi'+C +Qe ) by a transition factor [(CFRM) x (l-IER)x(l-DR)] to obtain Q4). Further, the proportion of molecules that will be inactive having incorporated K-l bases in N flows (Q7) may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the prior active or inactive states reaching the transition by the corresponding transition factors and adding the resulting quantities (e.g., multiplying (Qi'+C +Qe ) by a transition factor [CFRM x DR]) to obtain (¾ and multiplying (Q6+Q1 ' " ) by a transition factor [1- RMR] to obtain Q6", and adding Q5 and Q6" to obtain Q7) .
Phasing Models When Termination Chemistry Not Used
[0081] FIG. 6 illustrates schematically a simulation framework 120 for calculating predicted ionograms according to an embodiment in which termination chemistry is not utilized. In such an embodiment, for either the five or six parameters discussed above, RMR may be set to zero, and TFR may be set to one, and IMR (if being used) also may be set to zero. When the RMR is set to zero, the inactivated molecules need not be tracked because such molecules will no longer participate in any reactions. Accordingly, as before, the representation includes various steps and can be thought of as a matrix of flows (columns representing flows 1, 2, 3, and so on) and bases (rows representing bases 1, 2, 3, and so on). Again, bases may or may not incorporate in response to the flows, and simulations of incorporations (or absence thereof) generate paths along the cells of such a matrix. Docket No. LT00861 PCT
[0082] FIG. 7 illustrates an example cell 122 within a matrix as illustrated in FIG. 6, along with possible states and state transitions according to an embodiment. Such a cell 122 illustrates what may happen for an active molecule (e.g. , polymerase) present at the K-th base during the N-th flow. To arrive at this point, the molecule either incorporated base K-l in flow N or did not incorporate base K in flow N-l . There are then several possibilities. The molecule may undergo normal extension or a carry-forward event, and incorporate base K in flow N. The molecule may also fail to extend or undergo an incomplete extension event, and not incorporate base K in flow N. Finally, the molecule may become inactive and thus undergo droop. For a population of molecules, the proportion of molecules in the possible subsequent states will depend on the incoming populations and state transition parameters.
[0083] Referring to the exemplary cell 122 within a matrix as illustrated in FIG. 7, in situations where the K-th base matches the N-th flow, the proportion of molecules that will remain active and not incorporate base K in flow N (e.g., Q3) may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the two prior states (e.g.,
Q1+Q2) by a transition factor comprising term [IERx(l-DR)], where IER is an incomplete extension rate and DR is a droop rate. Conversely, the proportion of molecules that will remain active and incorporate base K in flow N (e.g., Q4) may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the two prior states (e.g., Q1+Q2) by a transition factor comprising term [(l-IER)x(l-DR)] .
[0084] Referring to the exemplary cell 122 within a matrix as illustrated in FIG. 7, in situations where the K-th base does not match the N-th flow, the proportion of molecules that will remain active and not incorporate base K in flow N (e.g., Q3) may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the two prior states Docket No. LT00861 PCT
(e.g., Q1+Q2) by a transition factor comprising term [(l-CFRM)+(CFRMxIERx(l-DR))], where CFR is a carry forward rate and M is the smallest number such that the (N-M)-th flow matches the K-th base. Conversely, the proportion of molecules that will remain active and incorporate base K in flow N (e.g., Q4) may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the two prior states (e.g., Q1+Q2) by a transition factor comprising term [CFRMx(l-IER)x(l-DR)] .
[0085] FIG. 8 illustrates schematically a simulation framework 130 for calculating predicted ionograms according to an embodiment in which the RMR rate, the TFR rate, and the IMR rate (if being modeled) are set to zero. By setting these parameters to zero, the dynamic
programming matrix reduces to an upper triangular matrix as shown in FIG. 8. As in the embodiment of FIGS. 6 and 7, when the RMR is set to zero, the inactivated molecules need not be tracked because such molecules will not participate in any reactions. Accordingly, as before, the representation includes various steps and can be thought of as a matrix of flows (columns representing flows 1, 2, 3, and so on) and bases (rows representing bases 1, 2, 3, and so on). Again, bases may or may not incorporate in response to the flows, and simulations of incorporations (or absence thereof) generate paths along the cells of such a matrix.
[0086] FIG. 9 illustrates an exemplary cell 132 within the matrix illustrated in FIG. 8, with possible molecule states and state transitions labeled, according to one disclosed embodiment. Such a cell illustrates what may happen for active molecules (e.g. , a molecule being actively synthesized during a flow with an active polymerase) present at the K-th base during the N-th nucleotide flow. To arrive at this point, active molecules include those that either incorporated base K-l in flow N or did not incorporate base K in flow N-l . In this model, the active molecules that incorporated base K-l in flow N (Qi in FIG. 9) are passed to juncture 89. The Docket No. LT00861 PCT active molecules that enter cell 132 due to a failure to incorporate base K in the N-l flow are represented by Q2 in FIG. 9, and this subset of active molecules is passed to juncture 86 in FIG. 9.
[0087] At juncture 86, one of three possibilities can occur. The active molecules may fail to extend or undergo incomplete extension, which is represented by Q8 in FIG. 9, and are passed to juncture 89; they may become inactive and undergo droop, which is represented by subset Q5 in FIG. 9; or they may undergo normal extension or a carry forward event and incorporate base K in flow N, which is represented by Q4 in FIG. 9, which becomes active molecules that have incorporated base K in flow N and move to the next cell along a flow column N.
[0088] Referring to the exemplary cell 80 within a matrix as illustrated in FIG. 9, in situations where the K-th base matches the N-th flow, the various transitions at the various junctures may be as follows: juncture 86 has one input (Q2) and three outputs (Q8 = (Q2) x [IER x (1 - DR)], Q5 = (Q2) x [DR], and Q4 = (Q2) x ([1 - IER] x [1 - DR])); juncture 89 has two inputs (Qi and Q8) and one output (Q3 = Qi + Q8).
[0089] Therefore, with respect to the outputs from the exemplary cell 80 (Q3 and Q4), Q3 may be determined directly or indirectly from prior states based on transition rate [IER x (1 - DR)], and Q4 may be determined directly or indirectly from prior states based on transition rate ([1 - IER] x [1 - DR]). The proportion of molecules that will remain active and not incorporate base K in flow N (Q3) may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the prior active states by the corresponding transition factors and adding the resulting quantities (e.g., multiplying (Q2) by a transition factor [IERx(l-DR)] to obtain Q8, and adding Q8 and Qi to obtain Q3). Conversely, the proportion of molecules that will remain active and incorporate base K in flow N (Q4) may be determined by multiplying some Docket No. LT00861 PCT measure of the quantity (e.g., number, concentration, etc.) of molecules in the active prior states by the corresponding transition factor (e.g., multiplying (Q2) by a transition factor
[(l-IER)x(l-DR)] to obtain Q4).
[0090] In situations where the K-th base does not match the N-th flow, the various transitions at the various junctures may be as follows: juncture 86 has one input (Q2) and three outputs (Q8 = (Q2) x [(1-CFRM)+CFRM x IER x (1 - DR)], Q5 = (Q2) x [DR], and Q4 = (Q2) x ([CFRM ] x [1 - IER] x [1 - DR]); juncture 89 has two inputs (Qi and Q8) and one output (Q3 = Qi + Q8).
Therefore, with respect to the outputs from the exemplary cell 80 (Q3 and Q4), Q3 may be determined directly or indirectly from prior states based on transition factor [(1-CFRM)+CFRM x IER x (1 - DR)], and Q4 may be determined directly or indirectly from prior states based on transition factor ([CFRM ] x [1 - IER] x [1 - DR]). The proportion of molecules that will remain active and not incorporate base K in flow N (Q3) may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the prior active states by the corresponding transition factors and adding the resulting quantities (e.g., multiplying (Q2) by a transition factor [(1-CFRM)+CFRM x IER x (1 - DR)] to obtain Q8, and adding Q8 and Ql to obtain Q3). Conversely, the proportion of molecules that will remain active and incorporate base K in flow N (Q4) may be determined by multiplying some measure of the quantity (e.g., number, concentration, etc.) of molecules in the active prior states by the corresponding transition factor (e.g., multiplying (Q2) by a transition factor [CFRM x (1 - IER) x (1 - DR)] to obtain Q4).
Simulation Studies
[0091] FIGS. 10A-10D, 11A-11D, and 12A-12D illustrate simulated plots showing a
comparison between the termination chemistry phasing models using the five parameters IER, CFR, DR, RMR, and TFR disclosed herein (shown by triangles and abbreviation "term" in Docket No. LT00861 PCT figures) and standard phasing models utilized for sequencing systems that do not employ termination chemistry (shown by circles and abbreviation "flow" in figures), both having the same simulated phasing errors. The embodiment detailed in FIGS. 6 and 7 was used to simulate standard phasing while the embodiment detailed in FIGS. 8 and 9 was used to simulate termination chemistry phasing. In the simulations presented, RMR was set to zero and TFR to less than 1. FIGS. 10A-10D illustrate plots showing the simulated results for a low noise level (with the noise standard deviations set at 0.03 additive, 0.03 multiplicative); FIGS. 11A-11D illustrate plots showing the simulated results for a medium noise level (with the noise standard deviations set at 0.1 additive, 0.05 multiplicative); and FIGS. 12A-12D illustrate plots showing the simulated results for a high noise level (with the noise standard deviations set at 0.2 additive, 0.05 multiplicative). As shown in the following figures, when experiencing the same phasing parameters, the termination chemistry model exhibits reduced error rates per flow as compared to the standard model. Further, based on the simulations presented, the termination chemistry models provided herein enable unexpected and significantly greater accuracy in the results for longer homopolymers.
[0092] Specifically, FIGS. 10A, 11A, and 12A illustrate an error rate versus homopolymer length for low, medium, and high noise levels, respectively. As shown in these plots, the termination chemistry error rate is significantly reduced compared to the standard error rate at each of the noise levels. FIGS. 10B, 1 IB, and 12B illustrate an error rate by flow for low, medium, and high noise levels, respectively. As shown in these plots, the termination chemistry models provided herein enable reduced errors rates per flow. FIGS. IOC, 11C, and 12C illustrate the number of flows it takes to sequence through the template for the low, medium, and high noise levels, respectively. FIGS. 10D, 1 ID, and 12D illustrate the average error rates per base Docket No. LT00861 PCT for the low, medium, and high noise levels, respectively, again showing the reduction in error rates with the termination chemistry model.
[0093] FIGS. 13A-13H, FIGS. 14A-14H, FIGS. 15A-15H, FIGS. 16A-16H, and FIGS. 17A-17H illustrate simulations comparing termination chemistry modeling and standard modeling for incomplete extension levels of 0.5, 1.5, 2.5, 3.5, and 4.5, respectively. Sets A-D and E-F simulate the same set of base sequences and phasing parameters for different nucleotide flow orders. The noise standard deviations were set at 0.05 additive, 0.05 multiplicative. As shown in the illustrated simulations, the termination chemistry model offers improved error rates for longer homopolymer lengths, as can be seen from FIGS. 13A,E, 14A,E, 15,A,E, 16,A,E.
Phasing effects accumulate over time so that later flows in general experience larger error rates than earlier flows. Even though using termination chemistry requires more total flows to sequence through a template sequence of a given length (see FIGS. C), the simulated peak error rate per flow (which always occurs in the later flows, towards the end of the template) does not exceed and generally stays significantly below the simulated peak error rate for non-terminator sequencing. The observed simulated error rates vary with the nucleotide flow order. For example, in FIG. 16B, the error peak for the termination chemistry model occurs at a later point than the error peak for the standard model and is lower in height. A similar effect is realized in FIGS. 17B and 17F in which the error rate remains low for the termination model for more flows than the standard model. In FIGS. 13D,H - 17D,H (with the exception of 17D) the termination chemistry model simulated results indicate lower per base error rates and thus higher overall base accuracy.
[0094] Further modifications and alternative embodiments will be apparent to those of ordinary skill in the art in view of the disclosure herein. For example, the systems and the methods may Docket No. LT00861 PCT include additional components or steps that were omitted from the diagrams and description for clarity of operation. Accordingly, this description is to be construed as illustrative only and is for the purpose of teaching those skilled in the art the general manner of carrying out the present disclosure. It is to be understood that the various embodiments shown and described herein are to be taken as exemplary. Elements and materials, and arrangements of those elements and materials, may be substituted for those illustrated and described herein, parts and processes may be reversed, and certain features of the present teachings may be utilized independently, all as would be apparent to one skilled in the art after having the benefit of the description herein. Changes may be made in the elements described herein without departing from the spirit and scope of the present teachings and following claims.
[0095] It is to be understood that the particular examples and embodiments set forth herein are non-limiting, and modifications to structure, dimensions, materials, and methodologies may be made without departing from the scope of the present teachings.
[0096] Other embodiments in accordance with the present disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. It is intended that the specification and examples be considered as exemplary only, with the claims being entitled to their full breadth and scope, including equivalents.

Claims

Docket No. LT00861 PCT CLAIMS What is claimed is:
1. A method for nucleic acid sequencing, comprising:
receiving observed or measured nucleic acid sequencing data from a sequencing instrument configured to receive a sample nucleic acid and to process the sample nucleic acid in a termination sequencing-by-synthesis process;
generating a set of candidate sequences of bases for the observed or measured nucleic acid sequencing data by determining a predicted signal for candidate sequences using a simulation framework for simulating possible state transitions for active and inactive molecules present at a K-th base during an N-th nucleotide flow, where K and N denote indices associated with bases and nucleotide flows, respectively, wherein the simulation framework for simulating the possible state transitions incorporates an estimated carry forward rate (CFR), an estimated incomplete extension rate (IER), an estimated droop rate (DR), an estimated reactivated molecules rate (RMR), and an estimated termination failure rate (TFR), the RMR being greater than or equal to zero and the TFR being lesser than one; and
identifying, from the set of candidate sequences of bases, one candidate sequence leading to optimization of a solver function as corresponding to the sequence for the sample nucleic acid.
2. The method of claim 1, wherein the simulation framework comprises simulating possible state transitions for situations where the K-th base matches the N-th nucleotide flow by modeling (i) a proportion of molecules that will remain active or become active and not incorporate base K Docket No. LT00861 PCT in flow N using a first set of state transition factors and (ii) a proportion of molecules that will remain active and incorporate base K in flow N using a second set of state transition factors.
3. The method of claim 2, wherein:
the first set of state transition factors comprises a state transition factor [1 - TFR], a state transition factor [TFR], a state transition factor [RMR], and a state transition factor [(IER x (1 - DR))]; and
the second set of state transition factors comprises a state transition factor [TFR], a state transition factor [RMR], and a state transition factor [(1 - IER) x (1 - DR)].
4. The method of claim 1, wherein the simulation framework comprises simulating possible state transitions for situations where the K-th base does not match the N-th nucleotide flow by modeling (i) a proportion of molecules that will remain active or become active and not incorporate base K in flow N using a first set of state transition factors and (ii) a proportion of molecules that will remain active and incorporate base K in flow N using a second set of state transition factors.
5. The method of claim 4, wherein:
the first set of state transition factors comprises a state transition factor [1 - TFR], a state transition factor [TFR], a state transition factor [RMR], and a state transition factor [(1 - CFRM) + (CFRMx IER x (1 - DR))]; and
the second set of state transition factors comprises a state transition factor [TFR], a state transition factor [RMR], and a state transition factor [CFRMx (1 - IER ) x (1 - DR)], where M is the smallest number such that the (N-M)-th flow matches the K-th base. Docket No. LT00861 PCT
6. The method of claim 1, wherein the termination sequencing-by-synthesis process comprises reversible termination sequencing utilizing a reversible terminator to reversibly terminate primer extension along the sample nucleic acid.
7. The method of claim 6, wherein the reversible terminator comprises a three prime O- blocked reversible terminator having a blocking group linked to the oxygen atom of the three prime hydroxyl group of the pentose of the reversible terminator.
8. The method of claim 6, wherein the reversible terminator comprises a three prime unblocked reversible terminator having an unblocked three prime hydroxyl group and a reversible terminating group linked to a base.
9. The method of claim 1, wherein the termination sequencing-by-synthesis process comprises irreversible termination sequencing utilizing an irreversible terminator to reversibly terminate primer extension along the sample nucleic acid, and the simulation framework for simulating the possible state transitions further incorporates an estimated inactivated molecules rate (IMR).
10. A nucleic acid sequencing system, comprising:
a sequencing instrument configured to receive a sample nucleic acid, at least one nucleotide having a terminating group, a primer, and a polymerase, and to process the sample nucleic acid in a termination sequencing-by-synthesis process to produce raw nucleic acid sequencing data;
a processor configured to receive the raw nucleic acid sequencing data and to generate a set of candidate sequences of bases for sample nucleic acid by determining a predicted signal for Docket No. LT00861 PCT candidate sequences using a simulation framework for simulating possible state transitions for active and inactive molecules present at a K-th base during an N-th nucleotide flow, where K and N denote indices associated with bases and nucleotide flows, respectively, wherein the simulation framework for simulating the possible state transitions incorporates an estimated carry forward rate (CFR), an estimated incomplete extension rate (IER), an estimated droop rate (DR), an estimated reactivated molecules rate (RMR), and an estimated termination failure rate (TFR), the RMR being at a value greater than or equal to zero and the TFR being at a value lesser than one.
11. The system of claim 10, wherein the RMR is at a value of zero and the TFR is at a value of zero.
12. The system of claim 10, wherein the processor is further configured to identify, from the set of candidate sequences of bases, one candidate sequence leading to optimization of a solver function as corresponding to the correct sequence for the sample nucleic acid.
13. The system of claim 10, further comprising a flow controller configured to control the timing and quantity of the flows of the sample nucleic acid, the at least one nucleotide having a terminating group, the primer, and the polymerase to the sequencing instrument.
14. The system of claim 13, wherein the at least one nucleotide comprises 2',3'
dideoxynucleotides in the form of ddATP, ddCTP, ddGTP, and ddTTP, and the flow controller is configured to flow a mixture of ddATP, ddCTP, ddGTP, and ddTTP concurrently into the sequencing instrument. Docket No. LT00861 PCT
15. The system of claim 13, wherein the at least one nucleotide comprises 2',3'
dideoxynucleotides in the form of ddATP, ddCTP, ddGTP, and ddTTP, and the flow controller is configured to flow each of ddATP, ddCTP, ddGTP, and ddTTP, one at a time, into the sequencing instrument.
16. The system of claim 13, wherein the sequencing instrument comprises an ion
semiconductor sequencing apparatus configured to detect hydrogen ions released during polymerization during synthesis of a nucleic acid strand complementary to the sample nucleic acid.
17. An apparatus, comprising:
a machine readable memory; and
a processor configured to execute machine-readable instructions, said instructions which when executed cause the apparatus to:
receive observed or measured nucleic acid sequencing data from a sequencing instrument configured to receive a sample nucleic acid and to process the sample nucleic acid in a termination sequencing-by-synthesis process; and
generate a set of candidate sequences of bases for the observed or measured nucleic acid sequencing data by determining a predicted signal for candidate sequences using a simulation framework for simulating possible state transitions for active and inactive molecules present at a K-th base during an N-th nucleotide flow, where K and N denote indices associated with bases and nucleotide flows, respectively, wherein the simulation framework for simulating the possible state transitions incorporates an estimated carry forward rate (CFR), an estimated incomplete extension rate (IER), an estimated droop rate (DR), an estimated reactivated molecules rate Docket No. LT00861 PCT
(RMR), and an estimated termination failure rate (TFR), and wherein the RMR is greater than or equal to zero and the TFR is lesser than one.
18. The apparatus of claim 17, wherein the processor is further configured to execute machine-readable instructions, said instructions which when executed cause the apparatus to identify, from the set of candidate sequences of bases, one candidate sequence leading to optimization of a solver function as corresponding to the correct sequence for the sample nucleic acid.
19. The apparatus of claim 17, wherein the TFR is zero.
20. The apparatus of claim 17, wherein the simulation framework for simulating the possible state transitions further incorporates an estimated inactivated molecules rate (IMR).
PCT/US2014/059191 2013-10-04 2014-10-03 Methods and systems for modeling phasing effects in sequencing using termination chemistry WO2015051338A1 (en)

Priority Applications (3)

Application Number Priority Date Filing Date Title
JP2016519836A JP6532456B2 (en) 2013-10-04 2014-10-03 Methods and systems for modeling PHASING EFFECTS in sequencing using termination chemistry
EP14790898.2A EP3053072B1 (en) 2013-10-04 2014-10-03 Methods and systems for modeling phasing effects in sequencing using termination chemistry
CN201480054627.3A CN105683980B (en) 2013-10-04 2014-10-03 The method and system of effect model stage by stage is established in using the sequencing for terminating chemical substance

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US201361886878P 2013-10-04 2013-10-04
US61/886,878 2013-10-04

Publications (1)

Publication Number Publication Date
WO2015051338A1 true WO2015051338A1 (en) 2015-04-09

Family

ID=51842844

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2014/059191 WO2015051338A1 (en) 2013-10-04 2014-10-03 Methods and systems for modeling phasing effects in sequencing using termination chemistry

Country Status (5)

Country Link
US (3) US10410739B2 (en)
EP (1) EP3053072B1 (en)
JP (1) JP6532456B2 (en)
CN (1) CN105683980B (en)
WO (1) WO2015051338A1 (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10410739B2 (en) 2013-10-04 2019-09-10 Life Technologies Corporation Methods and systems for modeling phasing effects in sequencing using termination chemistry
US11150179B2 (en) * 2017-01-06 2021-10-19 Illumina, Inc. Phasing correction

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2012058459A2 (en) * 2010-10-27 2012-05-03 Life Technologies Corporation Predictive model for use in sequencing-by-synthesis
US20130060482A1 (en) * 2010-12-30 2013-03-07 Life Technologies Corporation Methods, systems, and computer readable media for making base calls in nucleic acid sequencing

Family Cites Families (104)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4683195A (en) 1986-01-30 1987-07-28 Cetus Corporation Process for amplifying, detecting, and/or-cloning nucleic acid sequences
US4683202A (en) 1985-03-28 1987-07-28 Cetus Corporation Process for amplifying nucleic acid sequences
US4965188A (en) 1986-08-22 1990-10-23 Cetus Corporation Process for amplifying, detecting, and/or cloning nucleic acid sequences using a thermostable enzyme
US4800159A (en) 1986-02-07 1989-01-24 Cetus Corporation Process for amplifying, detecting, and/or cloning nucleic acid sequences
CA2020958C (en) 1989-07-11 2005-01-11 Daniel L. Kacian Nucleic acid sequence amplification methods
US6054034A (en) 1990-02-28 2000-04-25 Aclara Biosciences, Inc. Acrylic microchannels and their use in electrophoretic applications
US5210015A (en) 1990-08-06 1993-05-11 Hoffman-La Roche Inc. Homogeneous assay system using the nuclease activity of a nucleic acid polymerase
JP3080178B2 (en) 1991-02-18 2000-08-21 東洋紡績株式会社 Method for amplifying nucleic acid sequence and reagent kit therefor
US5587128A (en) 1992-05-01 1996-12-24 The Trustees Of The University Of Pennsylvania Mesoscale polynucleotide amplification devices
US6001229A (en) 1994-08-01 1999-12-14 Lockheed Martin Energy Systems, Inc. Apparatus and method for performing microfluidic manipulations for chemical analysis
US5750341A (en) 1995-04-17 1998-05-12 Lynx Therapeutics, Inc. DNA sequencing by parallel oligonucleotide extensions
US5854033A (en) 1995-11-21 1998-12-29 Yale University Rolling circle replication reporter systems
DK1179600T3 (en) 1996-06-04 2005-09-05 Univ Utah Res Found Hybridization monitoring during PCR
US6074827A (en) 1996-07-30 2000-06-13 Aclara Biosciences, Inc. Microfluidic method for nucleic acid purification and processing
GB9620209D0 (en) 1996-09-27 1996-11-13 Cemu Bioteknik Ab Method of sequencing DNA
GB9626815D0 (en) 1996-12-23 1997-02-12 Cemu Bioteknik Ab Method of sequencing DNA
US7348181B2 (en) 1997-10-06 2008-03-25 Trustees Of Tufts College Self-encoding sensor with microspheres
EP1032824A4 (en) 1997-10-15 2003-07-23 Aclara Biosciences Inc Laminate microstructure device and method for making same
US6780591B2 (en) 1998-05-01 2004-08-24 Arizona Board Of Regents Method of determining the nucleotide sequence of oligonucleotides and DNA molecules
WO1999057321A1 (en) 1998-05-01 1999-11-11 Arizona Board Of Regents Method of determining the nucleotide sequence of oligonucleotides and dna molecules
US7875440B2 (en) 1998-05-01 2011-01-25 Arizona Board Of Regents Method of determining the nucleotide sequence of oligonucleotides and DNA molecules
US6404907B1 (en) 1998-06-26 2002-06-11 Visible Genetics Inc. Method for sequencing nucleic acids with reduced errors
GB9901475D0 (en) 1999-01-22 1999-03-17 Pyrosequencing Ab A method of DNA sequencing
WO2000068671A2 (en) 1999-05-12 2000-11-16 Aclara Biosciences, Inc. Multiplexed fluorescent detection in microfluidic devices
US7211390B2 (en) 1999-09-16 2007-05-01 454 Life Sciences Corporation Method of sequencing a nucleic acid
US7244559B2 (en) 1999-09-16 2007-07-17 454 Life Sciences Corporation Method of sequencing a nucleic acid
US6274320B1 (en) 1999-09-16 2001-08-14 Curagen Corporation Method of sequencing a nucleic acid
EP1218543A2 (en) 1999-09-29 2002-07-03 Solexa Ltd. Polynucleotide sequencing
US6783934B1 (en) 2000-05-01 2004-08-31 Cepheid, Inc. Methods for quantitative analysis of nucleic acid amplification reaction
GB0016472D0 (en) 2000-07-05 2000-08-23 Amersham Pharm Biotech Uk Ltd Sequencing method and apparatus
WO2002019602A2 (en) 2000-09-01 2002-03-07 Fred Hutchinson Cancer Research Center Statistical modeling to analyze large data arrays
GB0022069D0 (en) 2000-09-08 2000-10-25 Pyrosequencing Ab Method
US6939451B2 (en) 2000-09-19 2005-09-06 Aclara Biosciences, Inc. Microfluidic chip having integrated electrodes
EP1384022A4 (en) 2001-04-06 2004-08-04 California Inst Of Techn Nucleic acid amplification utilizing microfluidic devices
JP4195859B2 (en) 2001-11-16 2008-12-17 株式会社バイオエックス FET type sensor, ion concentration detection method and base sequence detection method using the sensor
US7057026B2 (en) 2001-12-04 2006-06-06 Solexa Limited Labelled nucleotides
EP1706826A4 (en) 2002-01-25 2008-01-30 Applera Corp Methods for placing, accepting, and filling orders for products and services
US20030215816A1 (en) 2002-05-20 2003-11-20 Narayan Sundararajan Method for sequencing nucleic acids by observing the uptake of nucleotides modified with bulky groups
AU2003256298A1 (en) 2002-06-25 2004-01-06 Pel-Freez Clinical Systems, Llc Method for sequencing nucleic acids
US20040197845A1 (en) 2002-08-30 2004-10-07 Arjang Hassibi Methods and apparatus for pathogen detection, identification and/or quantification
US20040197793A1 (en) 2002-08-30 2004-10-07 Arjang Hassibi Methods and apparatus for biomolecule detection, identification, quantification and/or sequencing
US7575865B2 (en) 2003-01-29 2009-08-18 454 Life Sciences Corporation Methods of amplifying and sequencing nucleic acids
WO2005003375A2 (en) 2003-01-29 2005-01-13 454 Corporation Methods of amplifying and sequencing nucleic acids
US20060147935A1 (en) 2003-02-12 2006-07-06 Sten Linnarsson Methods and means for nucleic acid sequencing
GB0324456D0 (en) 2003-10-20 2003-11-19 Isis Innovation Parallel DNA sequencing methods
JP3903183B2 (en) 2004-02-03 2007-04-11 独立行政法人物質・材料研究機構 Gene detection field effect device and gene polymorphism analysis method using the same
EP1725574A4 (en) 2004-03-04 2008-10-29 Univ British Columbia Thrombomodulin (thbd) haplotypes predict outcome of patients
ITTO20040386A1 (en) 2004-06-09 2004-09-09 Infm Istituto Naz Per La Fisi FIELD-EFFECTIVE DEVICE FOR THE DETECTION OF SMALL QUANTITIES OF ELECTRIC CHARGE, SUCH AS THOSE GENERATED IN BIOMOLECULAR PROCESSES, IMMOBILIZED NEAR THE SURFACE.
AU2005275713B2 (en) 2004-08-24 2010-08-05 Tokyo Metropolitan Institute Of Medical Science Modified human hepatitis C virus genomic RNA having autonomous replicative competence
JP4608697B2 (en) 2004-08-27 2011-01-12 独立行政法人物質・材料研究機構 DNA base sequence analysis method and base sequence analysis apparatus using field effect device
TWI303714B (en) 2004-10-14 2008-12-01 Toshiba Kk Nucleic acid detecting sensor, nucleic acid detecting chip, and nucleic acid detecting circuit
US7424371B2 (en) 2004-12-21 2008-09-09 Helicos Biosciences Corporation Nucleic acid analysis
US7785862B2 (en) 2005-04-07 2010-08-31 454 Life Sciences Corporation Thin film coated microwell arrays
WO2006138257A2 (en) 2005-06-15 2006-12-28 Callida Genomics, Inc. Single molecule arrays for genetic and chemical analysis
JP4353958B2 (en) 2005-09-15 2009-10-28 株式会社日立製作所 DNA measuring apparatus and DNA measuring method
EP1971861A4 (en) * 2005-12-21 2014-10-22 Samsung Electronics Co Ltd Bio memory disc and bio memory disk drive apparatus, and assay method using the same
US8364417B2 (en) 2007-02-15 2013-01-29 454 Life Sciences Corporation System and method to correct out of phase errors in DNA sequencing data by use of a recursive algorithm
CN101390101B (en) 2006-02-16 2012-05-23 454生命科学公司 System and method for correcting primer extension errors in nucleic acid sequence data
JP4857820B2 (en) 2006-03-03 2012-01-18 学校法人早稲田大学 DNA sensing method
EP2071927A2 (en) 2006-09-28 2009-06-24 Illumina, Inc. Compositions and methods for nucleotide sequencing
CN101627129B (en) * 2006-10-06 2014-07-02 雀巢产品技术援助有限公司 Compositions and multiplex assays for measuring biological mediators of physiological health
EP2639578B1 (en) 2006-12-14 2016-09-14 Life Technologies Corporation Apparatus for measuring analytes using large scale fet arrays
US8349167B2 (en) 2006-12-14 2013-01-08 Life Technologies Corporation Methods and apparatus for detecting molecular interactions using FET arrays
US8262900B2 (en) 2006-12-14 2012-09-11 Life Technologies Corporation Methods and apparatus for measuring analytes using large scale FET arrays
US7932034B2 (en) 2006-12-20 2011-04-26 The Board Of Trustees Of The Leland Stanford Junior University Heat and pH measurement for sequencing of DNA
JP2010516285A (en) 2007-01-26 2010-05-20 イルミナ インコーポレイテッド Nucleic acid sequencing systems and methods
US8481259B2 (en) 2007-02-05 2013-07-09 Intelligent Bio-Systems, Inc. Methods and devices for sequencing nucleic acids in smaller batches
US20090105959A1 (en) 2007-06-01 2009-04-23 Braverman Michael S System and method for identification of individual samples from a multiplex mixture
CA2689626C (en) 2007-06-06 2016-10-25 Pacific Biosciences Of California, Inc. Methods and processes for calling bases in sequence by incorporation methods
WO2009005753A2 (en) 2007-06-28 2009-01-08 454 Life Sciences Corporation System and method for adaptive reagent control in nucleic acid sequencing
US8518640B2 (en) 2007-10-29 2013-08-27 Complete Genomics, Inc. Nucleic acid sequencing and process
US7767400B2 (en) 2008-02-03 2010-08-03 Helicos Biosciences Corporation Paired-end reads in sequencing by synthesis
US20100035253A1 (en) * 2008-03-19 2010-02-11 Intelligent Bio-Systems, Inc. Methods And Compositions For Incorporating Nucleotides
US7782237B2 (en) 2008-06-13 2010-08-24 The Board Of Trustees Of The Leland Stanford Junior University Semiconductor sensor circuit arrangement
GB2461127B (en) 2008-06-25 2010-07-14 Ion Torrent Systems Inc Methods and apparatus for measuring analytes using large scale FET arrays
EP2304420A4 (en) 2008-06-26 2013-10-30 Life Technologies Corp Methods and apparatus for detecting molecular interactions using fet arrays
US8407012B2 (en) 2008-07-03 2013-03-26 Cold Spring Harbor Laboratory Methods and systems of DNA sequencing
US20100035252A1 (en) 2008-08-08 2010-02-11 Ion Torrent Systems Incorporated Methods for sequencing individual nucleic acids under tension
US8383369B2 (en) 2008-09-24 2013-02-26 Pacific Biosciences Of California, Inc. Intermittent detection during analytical reactions
WO2010039553A1 (en) 2008-10-03 2010-04-08 Illumina, Inc. Method and system for determining the accuracy of dna base identifications
US20100137143A1 (en) 2008-10-22 2010-06-03 Ion Torrent Systems Incorporated Methods and apparatus for measuring analytes
US8546128B2 (en) 2008-10-22 2013-10-01 Life Technologies Corporation Fluidics system for sequential delivery of reagents
CN103901090B (en) 2008-10-22 2017-03-22 生命技术公司 Integrated sensor arrays for biological and chemical analysis
US20100301398A1 (en) 2009-05-29 2010-12-02 Ion Torrent Systems Incorporated Methods and apparatus for measuring analytes
US8370079B2 (en) * 2008-11-20 2013-02-05 Pacific Biosciences Of California, Inc. Algorithms for sequence determination
EP2359289A4 (en) 2008-11-26 2015-11-11 Illumina Inc Methods and systems for analysis of sequencing data
US9175338B2 (en) * 2008-12-11 2015-11-03 Pacific Biosciences Of California, Inc. Methods for identifying nucleic acid modifications
WO2010077859A2 (en) 2008-12-15 2010-07-08 Advanced Liquid Logic, Inc. Nucleic acid amplification and sequencing on a droplet actuator
WO2010075188A2 (en) 2008-12-23 2010-07-01 Illumina Inc. Multibase delivery for long reads in sequencing by synthesis protocols
US20100323348A1 (en) 2009-01-31 2010-12-23 The Regents Of The University Of Colorado, A Body Corporate Methods and Compositions for Using Error-Detecting and/or Error-Correcting Barcodes in Nucleic Acid Amplification Process
US8407554B2 (en) 2009-02-03 2013-03-26 Complete Genomics, Inc. Method and apparatus for quantification of DNA sequencing quality and construction of a characterizable model system using Reed-Solomon codes
US8772473B2 (en) 2009-03-30 2014-07-08 The Regents Of The University Of California Mostly natural DNA sequencing by synthesis
US8673627B2 (en) 2009-05-29 2014-03-18 Life Technologies Corporation Apparatus and methods for performing electrochemical reactions
WO2011091046A1 (en) 2010-01-19 2011-07-28 Verinata Health, Inc. Identification of polymorphic sequences in mixtures of genomic dna by whole genome sequencing
US20110257889A1 (en) 2010-02-24 2011-10-20 Pacific Biosciences Of California, Inc. Sequence assembly and consensus sequence determination
EP2580353B1 (en) 2010-06-11 2015-07-29 Life Technologies Corporation Alternative nucleotide flows in sequencing-by-synthesis methods
US10273540B2 (en) 2010-10-27 2019-04-30 Life Technologies Corporation Methods and apparatuses for estimating parameters in a predictive model for use in sequencing-by-synthesis
EP2659408B1 (en) 2010-12-29 2019-03-27 Life Technologies Corporation Time-warped background signal for sequencing-by-synthesis operations
WO2012092515A2 (en) 2010-12-30 2012-07-05 Life Technologies Corporation Methods, systems, and computer readable media for nucleic acid sequencing
EP3582224A1 (en) 2010-12-30 2019-12-18 Life Technologies Corporation Models for analyzing data from sequencing-by-synthesis operations
US20130090860A1 (en) 2010-12-30 2013-04-11 Life Technologies Corporation Methods, systems, and computer readable media for making base calls in nucleic acid sequencing
CN103764845B (en) 2011-04-08 2016-02-17 生命科技股份有限公司 For the synthesis of the reagent of the protection mutually stream sequence in order-checking
WO2014150392A1 (en) 2013-03-15 2014-09-25 Pacific Biosciences Of California, Inc. Methods and compositions for nucleic acid sequencing using electronic sensing elements
US10410739B2 (en) 2013-10-04 2019-09-10 Life Technologies Corporation Methods and systems for modeling phasing effects in sequencing using termination chemistry

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2012058459A2 (en) * 2010-10-27 2012-05-03 Life Technologies Corporation Predictive model for use in sequencing-by-synthesis
US20130060482A1 (en) * 2010-12-30 2013-03-07 Life Technologies Corporation Methods, systems, and computer readable media for making base calls in nucleic acid sequencing

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
D. GOLAN ET AL: "Using state machines to model the Ion Torrent sequencing process and to improve read error rates", BIOINFORMATICS, vol. 29, no. 13, 21 June 2013 (2013-06-21), pages i344 - i351, XP055158436, ISSN: 1367-4803, DOI: 10.1093/bioinformatics/btt212 *

Also Published As

Publication number Publication date
CN105683980A (en) 2016-06-15
US20150100247A1 (en) 2015-04-09
JP6532456B2 (en) 2019-06-19
EP3053072A1 (en) 2016-08-10
US20200043571A1 (en) 2020-02-06
CN105683980B (en) 2018-08-24
EP3053072B1 (en) 2024-02-21
US10410739B2 (en) 2019-09-10
US11636922B2 (en) 2023-04-25
US20230307095A1 (en) 2023-09-28
JP2016540279A (en) 2016-12-22

Similar Documents

Publication Publication Date Title
US20230307095A1 (en) Methods and systems for modeling phasing effects in sequencing using termination chemistry
US20240021272A1 (en) Systems and methods for identifying sequence variation
EP2553619B1 (en) System and method to correct out of phase errors in dna sequencing data by use of a recursive algorithm
EP2633470B1 (en) Predictive model for use in sequencing-by-synthesis
US20230131684A1 (en) Methods and Apparatuses for Estimating Parameters in a Predictive Model for Use in Sequencing-by-Synthesis
EP2002367B1 (en) System and method for correcting primer extension errors in nucleic acid sequence data
US20170335387A1 (en) Systems and methods for identifying sequence variation
US20210108254A1 (en) Methods and systems for reducing phasing errors when sequencing nucleic acids using termination chemistry
Das et al. Base-calling for Illumina's next-generation DNA sequencing systems via Viterbi algorithm
US11566281B2 (en) Systems and methods for paired end sequencing
Lee et al. Rapid and robust denoising of pyrosequenced amplicons for metagenomics

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 14790898

Country of ref document: EP

Kind code of ref document: A1

ENP Entry into the national phase

Ref document number: 2016519836

Country of ref document: JP

Kind code of ref document: A

NENP Non-entry into the national phase

Ref country code: DE

REEP Request for entry into the european phase

Ref document number: 2014790898

Country of ref document: EP

WWE Wipo information: entry into national phase

Ref document number: 2014790898

Country of ref document: EP