WO2022244058A1 - 塩基配列の解析方法及び遺伝子解析装置 - Google Patents
塩基配列の解析方法及び遺伝子解析装置 Download PDFInfo
- Publication number
- WO2022244058A1 WO2022244058A1 PCT/JP2021/018618 JP2021018618W WO2022244058A1 WO 2022244058 A1 WO2022244058 A1 WO 2022244058A1 JP 2021018618 W JP2021018618 W JP 2021018618W WO 2022244058 A1 WO2022244058 A1 WO 2022244058A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- correction amount
- mobility correction
- data
- amount data
- base sequence
- Prior art date
Links
- 108090000623 proteins and genes Proteins 0.000 title claims abstract description 57
- 238000000034 method Methods 0.000 title claims description 54
- 238000012937 correction Methods 0.000 claims abstract description 200
- 238000001962 electrophoresis Methods 0.000 claims abstract description 112
- 238000004458 analytical method Methods 0.000 claims abstract description 60
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 8
- 238000005457 optimization Methods 0.000 claims abstract description 8
- 238000013508 migration Methods 0.000 claims description 79
- 230000005012 migration Effects 0.000 claims description 79
- 238000012545 processing Methods 0.000 claims description 48
- 230000008569 process Effects 0.000 claims description 21
- 238000012252 genetic analysis Methods 0.000 claims description 12
- 238000012300 Sequence Analysis Methods 0.000 claims description 6
- 230000008859 change Effects 0.000 claims description 5
- 230000002068 genetic effect Effects 0.000 claims 3
- 238000005259 measurement Methods 0.000 abstract description 6
- 230000037230 mobility Effects 0.000 description 143
- 239000000523 sample Substances 0.000 description 54
- 238000003860 storage Methods 0.000 description 32
- 238000007405 data analysis Methods 0.000 description 29
- 238000010586 diagram Methods 0.000 description 21
- 238000001514 detection method Methods 0.000 description 19
- 108020004414 DNA Proteins 0.000 description 17
- 230000006870 function Effects 0.000 description 13
- 229920000642 polymer Polymers 0.000 description 11
- 239000007853 buffer solution Substances 0.000 description 9
- 238000004364 calculation method Methods 0.000 description 9
- 239000000872 buffer Substances 0.000 description 8
- 230000003287 optical effect Effects 0.000 description 7
- 238000005406 washing Methods 0.000 description 7
- 239000003153 chemical reaction reagent Substances 0.000 description 5
- 239000007850 fluorescent dye Substances 0.000 description 5
- 239000000243 solution Substances 0.000 description 5
- 238000004140 cleaning Methods 0.000 description 4
- 239000012634 fragment Substances 0.000 description 4
- 239000013642 negative control Substances 0.000 description 4
- 239000013641 positive control Substances 0.000 description 4
- 230000001419 dependent effect Effects 0.000 description 3
- 230000005284 excitation Effects 0.000 description 3
- 239000012530 fluid Substances 0.000 description 3
- 230000007246 mechanism Effects 0.000 description 3
- 238000000926 separation method Methods 0.000 description 3
- OPTASPLRGRRNAP-UHFFFAOYSA-N cytosine Chemical compound NC=1C=CNC(=O)N=1 OPTASPLRGRRNAP-UHFFFAOYSA-N 0.000 description 2
- 230000005684 electric field Effects 0.000 description 2
- 238000002474 experimental method Methods 0.000 description 2
- UYTPUPDQBNUYGX-UHFFFAOYSA-N guanine Chemical compound O=C1NC(N)=NC2=C1N=CN2 UYTPUPDQBNUYGX-UHFFFAOYSA-N 0.000 description 2
- 238000009434 installation Methods 0.000 description 2
- 238000013507 mapping Methods 0.000 description 2
- 229920001721 polyimide Polymers 0.000 description 2
- RWQNBRDOKXIBIV-UHFFFAOYSA-N thymine Chemical compound CC1=CNC(=O)NC1=O RWQNBRDOKXIBIV-UHFFFAOYSA-N 0.000 description 2
- 238000012546 transfer Methods 0.000 description 2
- 239000002699 waste material Substances 0.000 description 2
- 229930024421 Adenine Natural products 0.000 description 1
- GFFGJBXGBJISGV-UHFFFAOYSA-N Adenine Chemical compound NC1=NC=NC2=C1N=CN2 GFFGJBXGBJISGV-UHFFFAOYSA-N 0.000 description 1
- 108700028369 Alleles Proteins 0.000 description 1
- 239000004642 Polyimide Substances 0.000 description 1
- 230000004308 accommodation Effects 0.000 description 1
- 229960000643 adenine Drugs 0.000 description 1
- FFBHFFJDDLITSX-UHFFFAOYSA-N benzyl N-[2-hydroxy-4-(3-oxomorpholin-4-yl)phenyl]carbamate Chemical compound OC1=C(NC(=O)OCC2=CC=CC=C2)C=CC(=C1)N1CCOCC1=O FFBHFFJDDLITSX-UHFFFAOYSA-N 0.000 description 1
- 238000005251 capillar electrophoresis Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 239000000470 constituent Substances 0.000 description 1
- 238000011109 contamination Methods 0.000 description 1
- 238000001816 cooling Methods 0.000 description 1
- 229940104302 cytosine Drugs 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 230000006866 deterioration Effects 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 239000000428 dust Substances 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000008151 electrolyte solution Substances 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 239000011521 glass Substances 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 239000011810 insulating material Substances 0.000 description 1
- 230000001678 irradiating effect Effects 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- 239000003550 marker Substances 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 108020004707 nucleic acids Proteins 0.000 description 1
- 150000007523 nucleic acids Chemical class 0.000 description 1
- 102000039446 nucleic acids Human genes 0.000 description 1
- 239000002773 nucleotide Substances 0.000 description 1
- 125000003729 nucleotide group Chemical group 0.000 description 1
- 229920002401 polyacrylamide Polymers 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 229940113082 thymine Drugs 0.000 description 1
- 230000032258 transport Effects 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Images
Classifications
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12M—APPARATUS FOR ENZYMOLOGY OR MICROBIOLOGY; APPARATUS FOR CULTURING MICROORGANISMS FOR PRODUCING BIOMASS, FOR GROWING CELLS OR FOR OBTAINING FERMENTATION OR METABOLIC PRODUCTS, i.e. BIOREACTORS OR FERMENTERS
- C12M1/00—Apparatus for enzymology or microbiology
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING 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
- C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
- C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
- C12Q1/6869—Methods for sequencing
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
- G16B40/00—ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
- G16B40/10—Signal processing, e.g. from mass spectrometry [MS] or from PCR
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING 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
- C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
- C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
- C12Q1/6806—Preparing nucleic acids for analysis, e.g. for polymerase chain reaction [PCR] assay
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
- G16B30/00—ICT specially adapted for sequence analysis involving nucleotides or amino acids
Definitions
- the present invention relates to a gene analysis device and method for analyzing the base sequence of a sample using electrophoresis.
- the detection data of the reference base is used as the reference detection data
- the target peak that precedes and follows the reference peak of the reference detection data is selected from the other detection data (S7), and the target peak and the target peak (S8), and the shift amount of the target peak is calculated so that both peak intervals are equal (S9). correct the information (S10).”
- the base sequence of a nucleic acid is determined by including the following steps (A) to (C) in that order.
- a base peak extraction step of extracting base peaks from electrophoresis data containing peaks (B) setting search start base peaks and peak interval reference values for starting searches in time-series data composed of the extracted base peaks condition setting step (C) in the time-series data, starting from the search starting base peak, sequentially scanning between adjacent base peaks in the forward and backward directions of the time series, and determining the interval between the base peaks as the peak interval basis;
- the base sequence is determined by comparing the values and adding interpolated peaks to peak-missing sections.”
- the conventional mobility correction method functions correctly. For example, in the case of a sample containing a long mixed base sequence, or in the case of a signal containing a large amount of noise, the waveform of the signal is corrected to reduce waveform overlap, and there are cases where the correct base sequence cannot be identified.
- An object of the present invention is to provide a mobility correction method that solves the above problems.
- a representative example of the invention disclosed in the present application is as follows. That is, a method for analyzing a base sequence executed by a gene analyzer for analyzing the base sequence of a sample using time-series data of signal intensities of a plurality of bases obtained by electrophoresis of the sample, wherein the gene
- the analysis device manages an observation environment in association with mobility correction amount data for correcting the position in the time direction of the time-series data of the signal intensities of the plurality of bases
- the base sequence analysis method comprises: When the genetic analysis device receives time-series data of signal intensities of a plurality of bases obtained by electrophoresis of the sample under the first observation environment, it corresponds to the observation environment different from the first observation environment.
- FIG. 1 is a diagram showing a configuration example of a gene analysis apparatus of Example 1.
- FIG. 1 is a diagram showing a configuration example of an electrophoresis apparatus of Example 1.
- FIG. 4 is a diagram showing an example of migration characteristic information stored in the storage device of Example 1.
- FIG. 5 is a diagram showing an example of mobility correction amount information stored in a storage device according to the first embodiment;
- FIG. 5 is a diagram showing an example of mobility correction amount information stored in a storage device according to the first embodiment;
- FIG. 5 is a diagram showing an example of mobility correction amount information stored in a storage device according to the first embodiment;
- FIG. 4 is a flow chart for explaining an outline of processing executed by the gene analysis device of Example 1.
- FIG. 4 is a flow chart for explaining an outline of processing executed by the gene analysis device of Example 1.
- FIG. 4 is a flowchart for explaining electrophoresis processing executed by the electrophoresis apparatus of Example 1.
- FIG. 5 is a flowchart for explaining mobility correction processing executed by the data analysis device of the first embodiment;
- 4 is a diagram showing an image of a scale calculation method in Example 1.
- FIG. 4 is a diagram showing an image of scaling of mobility correction amount data in Example 1.
- FIG. 10 is a diagram showing an example of a method for correcting automatic mobility correction amount data according to the first embodiment;
- FIG. 10 is a diagram showing an example of a method for correcting automatic mobility correction amount data according to the first embodiment;
- FIG. 10 is a diagram showing a configuration example of a gene analysis apparatus of Example 2;
- 10 is a flowchart for explaining data generation processing executed by the gene analysis apparatus of Example 2.
- FIG. 10 is a flowchart for explaining mobility correction amount data generation processing executed by the gene analysis apparatus of Example 2.
- FIG. 10 is a diagram showing an image of migration characteristic data and mobility correction amount data stored
- FIG. 1 is a diagram showing a configuration example of the genetic analysis device 100 of Example 1.
- FIG. 1 is a diagram showing a configuration example of the genetic analysis device 100 of Example 1.
- the gene analysis device 100 includes an electrophoresis device 110 and a data analysis device 111.
- the electrophoresis device 110 and the data analysis device 111 are communicably connected using a communication cable.
- the data analysis device 111 has a control device 120 , a storage device 121 and a connection interface 122 .
- the control device 120 controls the electrophoresis apparatus 110 and performs data processing.
- the control device 120 is, for example, a CPU (Central Processing Unit) and a GPU (Graphics Processing Unit).
- the storage device 121 stores programs executed by the control device 120, setting information of the electrophoresis apparatus 110, information used for various processes, and the like.
- the storage device 121 is, for example, memory.
- connection interface 122 is an interface that connects with an input device and an output device, or an interface that connects with an external device via a network.
- the data analysis device 111 presents information to the user via the connection interface 122 and accepts information input by the user.
- the control device 120 operates as a sample information setting unit 131, an electrophoresis apparatus control unit 132, a fluorescence intensity calculation unit 133, a mobility correction unit 134, and a base call unit 135 by executing programs stored in the storage device 121. Operate. In the following description, when the processing is described with the functional unit as the subject, it means that the control device 120 is executing the program.
- the electrophoresis device 110 electrophoreses a sample (DNA fragment) and acquires migration data.
- the migration data is time-series data of luminance values of DNA fragments labeled with a fluorescent dye.
- FIG. 2 is a diagram showing a configuration example of the electrophoresis device 110 of the first embodiment.
- the electrophoresis apparatus 110 has a detection unit 216 , a constant temperature bath 218 , a carrier 225 , a high voltage power supply 204 , a first ammeter 205 , an anode-side electrode 211 , a second ammeter 212 , a capillary array 217 and a pump mechanism 203 .
- the capillary array 217 is a replacement member that includes a plurality of (e.g., eight) capillaries 202, and includes a load header 229, a detector 216, and a capillary head 233. Also, when the capillary 202 is damaged or degraded in quality, it can be replaced with a new capillary array 217 .
- the capillary 202 is composed of a glass tube with an inner diameter of several tens to several hundred microns and an outer diameter of several hundred microns, and its surface is coated with polyimide to improve its strength.
- the light irradiation portion irradiated with the laser light has a structure in which the polyimide film is removed so that the light emitted from the inside is easily leaked to the outside.
- the inside of the capillary 202 is filled with a separation medium for giving a migration velocity difference during electrophoresis. There are both fluid and non-fluid separation media, but in Example 1, a fluid polymer is used.
- a high voltage power supply 204 applies a high voltage to the capillary 202 .
- a first ammeter 205 detects the current emitted from the high-voltage power supply 204 .
- a second ammeter 212 detects the current flowing through the anode-side electrode 211 .
- the optical detection section for detecting the information light obtained from the sample is composed of a light source 214 for irradiating the detection section 216 with excitation light, an optical detector 215 for detecting light emission in the detection section 216, and a diffraction grating 232. there is
- the detector 216 is a member that acquires sample-dependent information.
- the detection unit 216 When detecting a sample in the capillary 202 separated by electrophoresis, the detection unit 216 is irradiated with excitation light from the light source 214 to generate fluorescence having a wavelength dependent on the sample as information light. Furthermore, the diffraction grating 232 disperses the information light in the wavelength direction, the optical detector 215 detects the disperse information light, and analyzes the sample.
- the capillary cathode ends 227 are fixed through metal hollow electrodes 226, and the tip of the capillary 202 protrudes from the hollow electrodes 226 by about 0.5 mm. Further, the hollow electrodes 226 provided in each capillary 202 are all integrated and attached to the load header 229 . Furthermore, all the hollow electrodes 226 are electrically connected to the high-voltage power supply 204 mounted on the main body of the apparatus, and function as cathode electrodes when it is necessary to apply voltage such as electrophoresis and sample introduction.
- the capillary end (other end) opposite to the capillary cathode end 227 is bundled together by a capillary head 233 .
- a capillary head 233 can be connected to block 207 in a pressure tight manner.
- a high voltage from the high voltage power supply 204 is applied between the load header 229 and the capillary head 233 .
- the new polymer is filled into the capillary 202 from the other end by the syringe 206 . Polymer refilling in capillary 202 is performed for each measurement to improve the performance of the measurement.
- the pump mechanism 203 is composed of a syringe 206 and a mechanical system for pressurizing the syringe 206, and injects the polymer into the capillary 202.
- a block 207 is a connecting portion for connecting the syringe 206, the capillary array 217, the anode buffer container 210, and the polymer container 209, respectively.
- the constant temperature bath 218 is covered with a heat insulating material and the temperature is controlled by a heating and cooling mechanism 220 in order to keep the capillary 202 in the constant temperature bath 218 at a constant temperature.
- a fan 219 circulates and agitates the air in the constant temperature bath 218 to keep the temperature of the capillary array 217 positionally uniform and constant.
- a transporter 225 transports various containers to the capillary cathode end 227 .
- the conveying machine 225 has three electric motors and linear actuators, and can move in three axial directions of up/down, left/right, and depth. At least one or more containers can be placed on the moving stage 230 of the carrier 225 .
- the motion stage 230 is equipped with motorized grips 231 for grasping and releasing each container. Therefore, the buffer container 221, washing container 222, waste container 223, and sample plate 224 can be transported to the capillary cathode end 227 as required. Unnecessary containers are stored in a predetermined accommodation within the electrophoresis apparatus 110 .
- a user can use the data analysis device 111 to control various functions of the electrophoresis device 110 and obtain migration data detected by the optical detection unit.
- the electrophoresis apparatus 110 may have a sensor for acquiring information (observation environment information) on the observation environment that affects electrophoresis.
- the electrophoresis apparatus 110 of FIG. 2 has an in-apparatus sensor 240 , a polymer sensor 241 and a buffer solution sensor 242 .
- the in-apparatus sensor 240 is a sensor for acquiring information about the internal environment of the electrophoresis apparatus 110, and measures, for example, a temperature sensor, a humidity sensor, and an air pressure sensor inside the electrophoresis apparatus 110.
- the polymer sensor 241 is a sensor for acquiring information about the quality of polymers, such as a PH sensor and an electrical conductivity sensor. Although the polymer sensor 241 is installed inside the polymer container 209 in FIG. 2, the installation location is not limited to this.
- the buffer solution sensor 242 is a sensor for acquiring information about the quality of the buffer solution, for example, a temperature sensor.
- the buffer solution sensor 242 is installed inside the anode buffer container 210 in FIG. 2, the installation location is not limited to this. For example, it may be set within the buffer container 221 .
- FIG. 3 is a diagram showing an example of migration characteristic information stored in the storage device 121 of the first embodiment.
- the storage device 121 stores migration characteristic information for managing migration characteristic data representing the relationship between migration time (t) and base position (p) for each type of base. Permanent characteristic data for each observation environment in the electrophoresis apparatus 110 is stored in the migration characteristic information.
- the migration characteristic data are managed as a function Y(p). In this embodiment, it is assumed that the parameters representing the functions are managed instead of the functions themselves.
- FIG. 3 shows migration characteristic data with different voltages applied by the high-voltage power supply 204 .
- Y 5 (p) is electrophoretic characteristic data at a voltage of 5.0 kV
- Y 8 (p) is electrophoretic characteristic data at a voltage of 8.0 kV
- Y 11 (p) is a voltage of 11.0 kV. It is migration characteristic data in the case of 0 kV.
- the migration characteristic information may be stored in the storage device 121 in advance, or may be obtained by electrophoresis of a sample having a known length such as a size standard in the electrophoresis device 110 by the electrophoresis device 110 . It may be generated using data.
- 4A, 4B, and 4C are diagrams showing examples of mobility correction amount information stored in the storage device 121 of the first embodiment.
- the storage device 121 stores mobility correction amount information for managing mobility correction amount data representing the relationship between migration time and mobility correction amount for each base species.
- the mobility correction amount information stores default mobility correction amount data for each observation environment in the electrophoresis apparatus 110 .
- the mobilities of base C (cytosine), base A (adenine), and base T (thymine) are corrected based on base G (guanine). Therefore, the storage device 121 stores the mobility correction amount information of each of base C, base A, and base T.
- FIG. 4A represents the mobility correction amount information of the base C
- FIG. 4B represents the mobility correction amount information of the base A
- FIG. 4C represents the mobility correction amount information of the base T.
- Curves represent default mobility correction amount data.
- the mobility correction amount information may be stored in the storage device 121 in advance, or may be obtained by actually performing electrophoresis of a sample having a known length such as a size standard in the electrophoresis apparatus 110 using the electrophoresis apparatus 110. may be generated using the migration data obtained from
- FIG. 5 is a flow chart explaining the outline of the processing executed by the gene analysis device 100 of the first embodiment.
- the electrophoresis device 110 of the gene analysis device 100 executes electrophoresis processing on the sample to be analyzed (step S101). Details of the electrophoresis process will be described with reference to FIG.
- the data analysis device 111 of the gene analysis device 100 executes fluorescence intensity calculation processing using migration data (step S102). Specifically, the fluorescence intensity calculator 133 calculates time-series data of the fluorescence intensity of the fluorescent dye from the migration data, and detects the center position, height, width, etc. of the peak from the time-series data of the fluorescence intensity.
- the data analysis device 111 of the gene analysis device 100 executes mobility correction processing on the fluorescence intensity time-series data (step S103). Details of the mobility correction process will be described with reference to FIGS. 7 to 10.
- FIG. The gene analysis apparatus 100 of Example 1 is characterized by mobility correction processing, as will be described later.
- the data analysis device 111 of the gene analysis device 100 performs a base call using the fluorescence intensity time-series data corrected based on the result of the mobility correction processing (step S104). Specifically, the base calling unit 135 identifies the base sequence of the sample using the time-series data of the corrected fluorescence intensity.
- FIG. 6 is a flowchart for explaining electrophoresis processing executed by the electrophoresis apparatus 110 of the first embodiment.
- the user sets the sample to be analyzed, reagents, etc. in the electrophoresis apparatus 110 and instructs the start of electrophoresis processing via the connection interface 122 .
- Samples are set according to the following procedure.
- the user fills the buffer container 221 and the anode buffer container 210 with a buffer solution that forms part of the current-carrying path.
- the buffer solution is, for example, an electrolytic solution commercially available for electrophoresis from each company.
- the user dispenses samples to be analyzed into the wells of the sample plate 224 .
- the sample is, for example, a PCR product of DNA.
- a user dispenses a cleaning solution into cleaning container 222 for cleaning capillary cathode end 227 .
- the cleaning solution is pure water, for example.
- a user injects an electrophoresis medium for electrophoresis of a sample into the syringe 206 .
- the electrophoresis medium is, for example, a polyacrylamide-based separation gel or polymer commercially available for electrophoresis from various companies.
- the user replaces the capillary array 217 when deterioration of the capillaries 202 is expected or when the length of the capillaries 202 is changed.
- the samples set on the sample plate 224 include, in addition to the actual sample of DNA to be analyzed, positive controls, negative controls, allelic ladders, and the like, which are electrophoresed in different capillaries 202 .
- a positive control is, for example, a PCR product containing known DNA, and is a sample for control experiments to confirm that the DNA is correctly amplified by PCR.
- a negative control is a PCR product that does not contain DNA, and is a control experiment sample for confirming that the amplified product of PCR is free from contamination such as user's DNA and dust.
- An allelic ladder is an artificial sample containing many bases that may generally be contained in a DNA marker, and is usually provided by a reagent manufacturer as a reagent kit for DNA identification. The allelic ladder is used for the purpose of fine-tuning the corresponding relationship between the DNA fragment lengths of individual DNA markers and alleles.
- a known DNA fragment labeled with a specific fluorescent dye is mixed with all of the real sample, positive control, negative control, and allelic ladder.
- the type of fluorescent dye assigned to the size standard differs depending on the reagent kit used.
- the user specifies the type of allelic ladder, the type of size standard, the type of fluorescent reagent, the type of sample set in the wells on the sample plate 224 corresponding to each capillary 202, and the like. In Example 1, any one type of real sample, positive control, negative control, and allelic ladder is specified. These information settings are input to the sample information setting unit 131 via the connection interface 122 of the data analysis device 111 .
- the electrophoresis apparatus control unit 132 transmits a signal instructing the start of analysis to the electrophoresis apparatus 110 . Upon receiving the signal, the electrophoresis apparatus 110 starts electrophoresis processing described below.
- the electrophoresis apparatus 110 first fills the capillary 202 with a new migration medium to form a migration path (step S201).
- the filling of the electrophoresis medium may be performed automatically after the analysis is started, or may be sequentially performed based on control signals transmitted from the electrophoresis apparatus control section 132 .
- the electrophoresis apparatus 110 carries the waste liquid container 223 directly under the load header 229 by the carrier 225, closes the solenoid valve 213, and receives the used electrophoresis medium discharged from the cathode end 227 of the capillary. to Then, the electrophoresis apparatus 110 drives the syringe 206 to fill the capillary 202 with a new electrophoresis medium and discard the used electrophoresis medium. Finally, the electrophoresis apparatus 110 immerses the capillary cathode end 227 in the washing solution in the washing container 222 to wash the capillary cathode end 227 dirty with the electrophoresis medium.
- the electrophoresis apparatus 110 applies a predetermined voltage to the migration medium to perform preliminary migration for making the migration medium suitable for electrophoresis (step S202).
- Preliminary electrophoresis may be performed automatically, or may be performed sequentially based on control signals transmitted from the electrophoresis apparatus controller 132 .
- the electrophoresis apparatus 110 immerses the cathode ends 227 of the capillaries in the buffer solution in the buffer container 221 by the transfer machine 225 to form an electric path. Then, the electrophoresis apparatus 110 applies a voltage of several to several tens of kilovolts to the migration medium for several to several tens of minutes using the high-voltage power supply 204 to make the migration medium suitable for electrophoresis. Finally, the electrophoresis apparatus 110 soaks the capillary cathode end 227 in the washing solution in the washing container 222 to wash the dirty capillary cathode end 227 with the buffer solution.
- the electrophoresis apparatus 110 introduces a sample (step S203).
- the introduction of the sample may be performed automatically, or sequentially based on control signals transmitted from the electrophoresis apparatus controller 132 .
- the electrophoresis apparatus 110 immerses the capillary cathode end 227 in the sample held in the well of the sample plate 224 by the carrier 225 and then opens the electromagnetic valve 213 . As a result, an energizing path is formed, and the sample component can be introduced into the electrophoresis path.
- the electrophoresis apparatus 110 applies a pulse voltage to the current path from the high-voltage power supply 204 to introduce sample components into the electrophoresis path.
- the electrophoresis apparatus 110 soaks the capillary cathode end 227 in the washing solution in the washing container 222 to wash the capillary cathode end 227 soiled by the sample.
- the electrophoresis apparatus 110 separates and analyzes each sample component contained in the sample to perform electrophoresis analysis (step S204).
- the electrophoresis analysis may be performed automatically, or sequentially based on control signals transmitted from the electrophoresis apparatus control section 132 .
- the electrophoresis apparatus 110 immerses the cathode ends 227 of the capillaries in the buffer solution in the buffer container 221 by the transfer machine 225 to form an electric path.
- the electrophoresis apparatus 110 applies a high voltage of about 15 kV to the current path by the high-voltage power supply 204 to generate an electric field in the electrophoresis path. Due to the generated electric field, each sample component in the migration path moves to the detection section 216 at a speed depending on the properties of each sample component. That is, sample components are separated by differences in their migration speeds. Then, the sample components that have reached the detection unit 216 are detected in order.
- the migration speed will differ depending on the base lengths, and DNAs with shorter base lengths will reach the detector 216 in order.
- Each DNA is attached with a fluorescent dye depending on its terminal base sequence.
- Electrophoresis device 110 detects fluorescence with optical detector 215 .
- the optical detector 215 detects this fluorescence at regular time intervals and transmits image data to the data analysis device 111 .
- each capillary 202 may transmit luminance values sampled only at wavelength positions at regular intervals.
- the data transmitted from the electrophoresis apparatus 110 is time-series data of luminance values of the capillaries 202 and stored in the storage device 121 .
- the electrophoresis apparatus 110 stops applying the voltage and ends the electrophoresis analysis.
- the above is the description of the electrophoresis treatment.
- FIG. 7 is a flowchart for explaining mobility correction processing executed by the data analysis device 111 of the first embodiment.
- FIG. 8 is a diagram showing an image of a scale calculation method according to the first embodiment.
- FIG. 9 is a diagram showing an image of scaling of mobility correction amount data according to the first embodiment.
- 10A and 10B are diagrams illustrating an example of a method for correcting automatic mobility correction amount data according to the first embodiment.
- the mobility correction unit 134 calculates the scale based on the observation environment information of the electrophoresis device 110 (step S301).
- a method of calculating the scale will be described by focusing on the voltage in the observation environment.
- the mobility correction unit 134 refers to the migration characteristic information and searches for migration characteristic data corresponding to the voltage (target voltage) included in the observation environment information. If migration characteristic data corresponding to the target voltage exists, default mobility correction amount data corresponding to the target voltage exists, so the mobility correction unit 134 terminates the processing of step S301. In this case, no scale calculation is performed.
- the mobility correction unit 134 uses the migration characteristic data of a voltage with a small difference from the target voltage to obtain the migration characteristic data of the target voltage (target migration characteristics data).
- the migration characteristic data of the actual observation environment is estimated using the migration characteristic data of the observation environment similar to the actual observation environment.
- the similarity of the viewing environment means that the combination of physical quantities representing the viewing environment is similar.
- the target voltage is 9.0 kV , as shown in FIG. Migration property data is generated.
- the electrophoresis characteristic data of the target voltage can be generated by Equation (1).
- the mobility correction unit 134 calculates the scale between the migration characteristic data used to generate the target migration characteristic data and the target migration characteristic data at time t.
- the scale S 8 (t) for the migration characteristic data Y 8 (p) of 8.0 kV at time t is given by equation (2)
- the scale S 8 (t) of 11.0 kV at time t is given by Equation (3).
- the mobility correction unit 134 generates default mobility correction amount data (step S302).
- a method of calculating the default mobility correction amount data will be described by focusing on the voltage in the observation environment.
- the mobility correction unit 134 refers to the mobility correction amount information of each base and searches for default mobility correction amount data corresponding to the voltage (target voltage) included in the observation environment information. If there is default mobility correction amount data corresponding to the target voltage, the mobility correction unit 134 ends the processing of step S302. In this case, the searched default mobility correction amount data is used as it is.
- the mobility correction unit 134 specifies the voltage of the migration characteristic data used to generate the target migration characteristic data in step S301. do.
- the mobility correction unit 134 refers to the mobility correction amount information of each base and acquires default mobility correction amount data corresponding to the specified voltage.
- the mobility correction unit 134 multiplies each point of the default mobility correction amount data by a scale corresponding to the specified voltage, thereby obtaining the default mobility of the target voltage. Calculate correction amount data.
- the mobility correction unit 134 multiplies the default mobility correction amount data of 8.0 kV by the scale S 8 (t) to obtain the first default mobility correction amount data. Then, the default mobility correction amount data of 11.0 kV is multiplied by the scale S 11 (t) to calculate the second default mobility correction amount data. Further, the mobility correction unit 134 calculates the average of the first default mobility correction amount data and the second default mobility correction amount data as default mobility correction amount data of 9.0 kV.
- the default mobility correction amount data for each observation environment in Example 1 has a scale relationship.
- the mobility correction unit 134 optimizes the amount of mobility correction for the fluorescence intensity time-series data (step S303).
- a known algorithm for optimizing the amount of mobility correction can be used for optimizing the amount of mobility correction, so a detailed description will be omitted.
- the following optimization algorithm is conceivable.
- the mobility correction unit 134 sets a block of a predetermined time size and moves the block in the time direction with respect to the fluorescence intensity time-series data so that the waveform overlap of each base in the block is minimized. Search for the mobility correction amount for each base.
- Mobility correction amount data (automatic mobility correction amount data) is obtained by plotting the results of the search processing and smoothly interpolating between the plotted points.
- the default mobility correction amount data may be used as an initial value for optimization.
- the mobility correction unit 134 determines mobility correction amount data based on the automatic mobility correction amount data and the default mobility correction amount data (step S304). For example, the following processing can be considered.
- the mobility correction unit 134 adopts the default mobility correction amount data.
- a unit 134 employs the automatic mobility correction amount data. The aforementioned difference is based on the maximum value of the difference between the automatic mobility correction amount data and the default mobility correction amount data, the total value of the differences at each point of the automatic mobility correction amount data and the default mobility correction amount data, etc. can be evaluated. For portions where the difference between the automatic mobility correction amount data and the default mobility correction amount data is small, the automatic mobility correction amount data is adopted, and the difference between the automatic mobility correction amount data and the default mobility correction amount data is The default mobility correction amount data may be employed for the portion where is large.
- the mobility correction unit 134 has a large difference between the automatic mobility correction amount data (solid line graph) and the default mobility correction amount data (dotted line graph), and A place (dotted-line rectangular area) with a large rate of change is identified. As shown in FIG. 10B , the mobility correction unit 134 corrects the specified location so that the difference from the default mobility correction amount data is small and the variation rate is small.
- the amount of mobility correction is calculated so that the overlap is reduced. Therefore, when the mixed base sequence is long, an appropriate mobility correction may not be calculated. In such a case, the difference from the default mobility correction amount data tends to increase.
- the mobility correction unit 134 of the first embodiment performs automatic correction using the default mobility correction amount data as correction constraints. This makes it possible to accurately correct the mobility even for a sample containing a long mixed base sequence or electrophoresis data containing a large amount of noise.
- the mobility correction amount data that is actually used is adjusted based on the default mobility correction amount data, part or all of it has characteristics similar to the default mobility correction amount data.
- Example 1 default mobility correction amount data for an arbitrary observation environment is generated by scaling default mobility correction amount data for different observation environments. This makes it possible to adapt to various observation environments.
- Example 2 the data analysis device 111 generates migration characteristic data and default mobility correction amount data for each observation environment.
- the second embodiment will be described below, focusing on the differences from the first embodiment.
- FIG. 11 is a diagram showing a configuration example of the gene analysis device 100 of Example 2.
- FIG. 11 is a diagram showing a configuration example of the gene analysis device 100 of Example 2.
- the configuration of the electrophoresis apparatus 110 of Example 2 is the same as that of Example 1.
- the hardware configuration of the data analysis device 111 of the second embodiment is the same as that of the first embodiment.
- the software configuration of the data analysis device 111 of Example 2 is partially different. Specifically, the data analysis apparatus 111 of the second embodiment differs from that of the first embodiment in that it has a migration characteristic data generator 136 .
- the migration characteristic data generator 136 generates migration characteristic data and default mobility correction amount data.
- the processing executed by the gene analysis apparatus 100 of the second embodiment is the same as that of the first embodiment.
- the electrophoresis process executed by the electrophoresis apparatus 110 of the second embodiment is the same as that of the first embodiment.
- the mobility correction processing executed by the data of the second embodiment is the same as that of the first embodiment.
- the storage device 121 stores reference migration characteristic data, mobility correction amount data, and base sequences of any sample in any observation environment.
- the sample is desirably a sample with a single nucleotide sequence that facilitates base calling.
- FIG. 12 is a flowchart for explaining data generation processing executed by the gene analysis device 100 of the second embodiment.
- the gene analysis apparatus 100 Upon receiving an instruction from the user, the gene analysis apparatus 100 executes data generation processing.
- the gene analysis apparatus 100 executes mobility correction amount data generation processing (step S401).
- mobility correction amount data generation process mobility correction amount data is generated for a plurality of observation environments, and a base call is performed for base sequences. Details of the processing will be described with reference to FIG.
- the gene analysis device 100 performs mapping between the reference base sequence and base sequences in any observation environment (step S402).
- the migration characteristic data generation unit 136 of the data analysis device 111 calculates the base position of base G in the base sequence of each observation environment by the above mapping.
- step S403 the gene analysis apparatus 100 executes migration characteristic data generation processing. Specifically, the following processing is executed.
- the migration characteristic data generation unit 136 of the data analysis device 111 plots points in a space with base positions and migration times as axes, based on the base sequence in a certain observation environment.
- the migration characteristic data generation unit 136 may interpolate between the points plotted in S403-1 as necessary.
- the migration characteristic data generator 136 obtains an approximate expression from the plotted points.
- the migration characteristic data generator 136 stores the parameters of the approximation formula as migration characteristic data in the storage device 121 in association with the observation environment.
- FIG. 13 is a flowchart for explaining mobility correction amount data generation processing executed by the gene analysis apparatus 100 of the second embodiment.
- the electrophoresis device 110 of the gene analysis device 100 executes sample electrophoresis processing for a plurality of observation environments (step S501).
- the electrophoresis treatment in Example 2 is the same as in Example 1.
- observation environment is assumed to be specified by the user. It is assumed that a plurality of pieces of electrophoresis data are obtained by executing the electrophoresis process a plurality of times for one observation environment.
- the data analysis device 111 of the gene analysis device 100 starts loop processing of the observation environment (step S502). Specifically, the data analysis device 111 selects one observation environment.
- the data analysis device 111 of the gene analysis device 100 executes fluorescence intensity calculation processing for a plurality of migration data (step S503).
- the fluorescence intensity calculation process of the second embodiment is the same as that of the first embodiment.
- the data analysis device 111 of the gene analysis device 100 optimizes the mobility correction amount for the time-series data of each fluorescence intensity (step S504).
- a well-known technique is used for optimizing the mobility correction amount in the second embodiment.
- the data analysis device 111 of the gene analysis device 100 performs a base call using the corrected time-series data of fluorescence intensity (step S505).
- the data analysis device 111 of the gene analysis device 100 generates mobility correction amount data of the observation environment (step S506).
- the migration characteristic data generator 136 calculates the average of the plurality of mobility correction amount data calculated in step S504.
- the migration characteristic data generator 136 stores the calculated mobility correction amount data in the storage device 121 in association with the observation environment. Note that the mobility correction amount data for which the base call of the base sequence is determined to be erroneous is excluded.
- the data analysis device 11 of the gene analysis device 100 determines whether or not processing has been completed for all observation environments (step S507).
- the data analysis device 111 of the genetic analysis device 100 returns to step S502 and performs similar processing.
- the gene analysis apparatus 100 terminates the mobility correction amount data generation processing.
- the second embodiment by preparing migration characteristic data for a plurality of observation environments, it is possible to reduce the cost of calculating the scale and calculating the mobility correction amount data.
- Example 3 the data analysis device 111 adds the migration characteristic data and the mobility correction amount calculated in the actual analysis.
- the third embodiment will be described below, focusing on the differences from the first embodiment.
- the configuration of the genetic analysis device 100 of Example 3 is the same as that of Example 1.
- the configurations of the electrophoresis device 110 and the data analysis device 111 of the third embodiment are the same as those of the first embodiment.
- Example 3 the processing executed by the gene analysis device 100 is partially different. Specifically, after the data analysis device 111 makes a base call (step S104), based on the user's instruction, the migration characteristic data and the mobility correction amount data calculated in a series of processes are transferred to the observation environment. They are stored in the storage device 121 in association with each other.
- FIG. 14 is a diagram showing an image of migration characteristic data and mobility correction amount data stored in the storage device 121 of the third embodiment.
- FIG. 14 shows the distribution of spatial data representing the observation environment composed of temperature and voltage.
- the initial storage device 121 stores permanent characteristic data and mobility correction amount data of the observation environment corresponding to the black dot. It can be seen that the permanent characteristic data and the mobility correction amount data of the observation environment indicated by hatched circles have been added by the user's instruction.
- Example 3 The electrophoresis process and mobility correction process of Example 3 are the same as those of Example 1. Also, the gene analysis apparatus 100 of Example 3 may execute data generation processing.
- Example 3 by adding the migration characteristic data and the mobility correction amount data according to the secular change of the gene analysis device 100 and the environment in which it is actually used, the accuracy and cost of base calling can be reduced. can.
- the present invention is not limited to the above-described embodiments, and includes various modifications. Further, for example, the above-described embodiments are detailed descriptions of the configurations for easy understanding of the present invention, and are not necessarily limited to those having all the described configurations. Moreover, it is possible to add, delete, or replace a part of the configuration of each embodiment with another configuration.
- each of the above configurations, functions, processing units, processing means, etc. may be realized in hardware, for example, by designing a part or all of them with an integrated circuit.
- the present invention can also be implemented by software program code that implements the functions of the embodiments.
- a computer is provided with a storage medium recording the program code, and a processor included in the computer reads the program code stored in the storage medium.
- the program code itself read from the storage medium implements the functions of the above-described embodiments, and the program code itself and the storage medium storing it constitute the present invention.
- Examples of storage media for supplying such program code include flexible disks, CD-ROMs, DVD-ROMs, hard disks, SSDs (Solid State Drives), optical disks, magneto-optical disks, CD-Rs, magnetic tapes, A nonvolatile memory card, ROM, or the like is used.
- program code that implements the functions described in this embodiment can be implemented in a wide range of programs or script languages, such as assembler, C/C++, perl, Shell, PHP, Python, and Java.
- the program code of the software that implements the functions of the embodiment can be stored in storage means such as a hard disk or memory of a computer, or in a storage medium such as a CD-RW or CD-R.
- a processor provided in the computer may read and execute the program code stored in the storage means or the storage medium.
- control lines and information lines indicate those that are considered necessary for explanation, and not all the control lines and information lines are necessarily indicated on the product. All configurations may be interconnected.
Landscapes
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Organic Chemistry (AREA)
- Proteomics, Peptides & Aminoacids (AREA)
- Wood Science & Technology (AREA)
- Zoology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Biotechnology (AREA)
- Physics & Mathematics (AREA)
- General Health & Medical Sciences (AREA)
- Biophysics (AREA)
- Molecular Biology (AREA)
- Biochemistry (AREA)
- Genetics & Genomics (AREA)
- Microbiology (AREA)
- General Engineering & Computer Science (AREA)
- Analytical Chemistry (AREA)
- Immunology (AREA)
- Medical Informatics (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Artificial Intelligence (AREA)
- Evolutionary Computation (AREA)
- Medicinal Chemistry (AREA)
- Biomedical Technology (AREA)
- Bioethics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- Epidemiology (AREA)
- Signal Processing (AREA)
- Sustainable Development (AREA)
- Public Health (AREA)
- Software Systems (AREA)
- Bioinformatics & Computational Biology (AREA)
- Evolutionary Biology (AREA)
- Theoretical Computer Science (AREA)
- Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
- Investigating, Analyzing Materials By Fluorescence Or Luminescence (AREA)
Abstract
Description
Claims (15)
- サンプルを電気泳動することによって取得される複数の塩基の信号強度の時系列データを用いて前記サンプルの塩基配列を解析する遺伝子解析装置が実行する塩基配列の解析方法であって、
前記遺伝子解析装置は、観測環境と、前記複数の塩基の信号強度の時系列データの時間方向の位置を補正するための移動度補正量データとを対応づけて管理し、
前記塩基配列の解析方法は、
前記遺伝子解析装置が、第1観測環境下において前記サンプルを電気泳動することによって取得された複数の塩基の信号強度の時系列データを受け付けた場合、前記第1観測環境と異なる前記観測環境に対応する前記移動度補正量データをスケーリングすることによって、デフォルト移動度補正量データを生成する第1のステップと、
前記遺伝子解析装置が、移動度補正量の最適化アルゴリズムと、前記デフォルト移動度補正量データとを用いて、前記複数の塩基の信号強度の時系列データの時間方向の位置を補正する第2のステップと、
補正された前記複数の塩基の信号強度の時系列データを用いて前記サンプルの塩基配列を特定する第3のステップと、を含むことを特徴とする塩基配列の解析方法。 - 請求項1に記載の塩基配列の解析方法であって、
前記遺伝子解析装置は、観測環境と、電気泳動による前記塩基の位置と泳動時間との関係を表す泳動特性データとを対応づけて管理し、
前記第1のステップは、
前記遺伝子解析装置が、前記第1観測環境に対応する前記泳動特性データと、前記第1観測環境とは異なる前記観測環境に対応する前記泳動特性データとを用いて、スケールを算出するステップと、
前記遺伝子解析装置が、前記スケールに基づいて、前記第1観測環境とは異なる前記観測環境に対応する前記移動度補正量データをスケーリングするステップと、を含むことを特徴とする塩基配列の解析方法。 - 請求項1に記載の塩基配列の解析方法であって、
前記第2のステップは、
前記遺伝子解析装置が、前記移動度補正量の最適化アルゴリズムに基づいて、自動移動度補正量データを生成する第4のステップと、
前記遺伝子解析装置が、前記自動移動度補正量データと前記デフォルト移動度補正量データとの差異に基づいて、前記自動移動度補正量データを補正する第5のステップと、を含むことを特徴とする塩基配列の解析方法。 - 請求項3に記載の塩基配列の解析方法であって、
前記第5のステップは、前記自動移動度補正量データと前記デフォルト移動度補正量データとの全体の差異が大きい場合、前記遺伝子解析装置が、前記自動移動度補正量データを前記デフォルト移動度補正量データに置き換えるステップを含むことを特徴とする塩基配列の解析方法。 - 請求項3に記載の塩基配列の解析方法であって、
前記第5のステップは、
前記遺伝子解析装置が、前記自動移動度補正量データと前記デフォルト移動度補正量データとの差異が大きい部分を特定するステップと、
前記遺伝子解析装置が、前記特定された部分を前記デフォルト移動度補正量データに置き換えるステップを含むことを特徴とする塩基配列の解析方法。 - 請求項3に記載の塩基配列の解析方法であって、
前記第5のステップは、
前記遺伝子解析装置が、前記自動移動度補正量データと前記デフォルト移動度補正量データとの差異が大きく、かつ、変動率が大きい部分を特定するステップと、
前記遺伝子解析装置が、前記特定された部分を、前記デフォルト移動度補正量データとの差異が小さくなるように補正するステップと、を含むことを特徴とする塩基配列の解析方法。 - 請求項1に記載の塩基配列の解析方法であって、
前記第3のステップは、前記遺伝子解析装置が、前記第1観測環境と、使用した前記移動度補正量データとを対応づけて保存するステップを含むことを特徴とする塩基配列の解析方法。 - 請求項2に記載の塩基配列の解析方法であって、
前記遺伝子解析装置が、第2観測環境下において前記サンプルを電気泳動することによって取得された複数の塩基の信号強度の時系列データの移動度補正量データと、補正された前記複数の塩基の信号強度の時系列データを用いて特定された前記サンプルの前記塩基配列と、を用いて、前記第2観測環境における前記複数の塩基の前記泳動特性データを生成するステップと、
前記第2観測環境と、前記生成された泳動特性データとを対応づけて保存するステップと、を含むことを特徴とする塩基配列の解析方法。 - サンプルを電気泳動することによって取得される複数の塩基の信号強度の時系列データを用いて前記サンプルの塩基配列を解析する遺伝子解析装置であって、
観測環境と、前記複数の塩基の信号強度の時系列データの時間方向の位置を補正するための移動度補正量データとを対応づけて管理し、
第1観測環境下において前記サンプルを電気泳動することによって取得された複数の塩基の信号強度の時系列データを受け付けた場合、前記第1観測環境と異なる前記観測環境に対応する前記移動度補正量データをスケーリングすることによって、デフォルト移動度補正量データを生成する第1の処理と、
移動度補正量の最適化アルゴリズムと、前記デフォルト移動度補正量データとを用いて、前記複数の塩基の信号強度の時系列データの時間方向の位置を補正する第2の処理と、
補正された前記複数の塩基の信号強度の時系列データを用いて前記サンプルの塩基配列を特定する第3の処理と、を実行することを特徴とする遺伝子解析装置。 - 請求項9に記載の遺伝子解析装置であって、
観測環境と、電気泳動による前記塩基の位置と泳動時間との関係を表す泳動特性データとを対応づけて管理し、
前記第1の処理では、
前記第1観測環境に対応する前記泳動特性データと、前記第1観測環境とは異なる前記観測環境に対応する前記泳動特性データとを用いて、スケールを算出し、
前記スケールに基づいて、前記第1観測環境とは異なる前記観測環境に対応する前記移動度補正量データをスケーリングすることを特徴とする遺伝子解析装置。 - 請求項9に記載の遺伝子解析装置であって、
前記第2の処理では、
前記移動度補正量の最適化アルゴリズムに基づいて、自動移動度補正量データを生成する第4の処理と、
前記自動移動度補正量データと前記デフォルト移動度補正量データとの差異に基づいて、前記自動移動度補正量データを補正する第5の処理と、を実行することを特徴とする遺伝子解析装置。 - 請求項11に記載の遺伝子解析装置であって、
前記第5の処理では、前記自動移動度補正量データと前記デフォルト移動度補正量データとの全体の差異が大きい場合、前記自動移動度補正量データを前記デフォルト移動度補正量データに置き換えることを特徴とする遺伝子解析装置。 - 請求項11に記載の遺伝子解析装置であって、
前記第5の処理では、
前記自動移動度補正量データと前記デフォルト移動度補正量データとの差異が大きい部分を特定し、
前記特定された部分を前記デフォルト移動度補正量データに置き換えることを特徴とする遺伝子解析装置。 - 請求項11に記載の遺伝子解析装置であって、
前記第5の処理では、
前記自動移動度補正量データと前記デフォルト移動度補正量データとの差異が大きく、かつ、変動率が大きい部分を特定し、
前記特定された部分を、前記デフォルト移動度補正量データとの差異が小さくなるように補正することを特徴とする遺伝子解析装置。 - サンプルの塩基配列を解析する遺伝子解析装置が実行する塩基配列の解析方法であって、
前記遺伝子解析装置が、第1観測環境下において前記サンプルを電気泳動することによって取得された複数の塩基の信号強度の時系列データを受け付けた場合、前記第1観測環境のデフォルト移動度補正量データを算出するステップと、
前記遺伝子解析装置が、前記デフォルト移動度補正量データを用いて、前記複数の塩基の信号強度の時系列データの時間方向の位置を補正するステップと、
前記遺伝子解析装置が、補正された前記複数の塩基の信号強度の時系列データを用いて前記サンプルの塩基配列を特定するステップと、を含み、
異なる観測環境の前記デフォルト移動度補正量データは、任意のスケールによって対応付けが可能なデータであり、
前記補正に用いた移動度補正量データは、少なくとも一部が、前記デフォルト移動度補正量データと類似する補正量の変化特性を有することを特徴とする塩基配列の解析方法。
Priority Applications (6)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
DE112021007137.8T DE112021007137T5 (de) | 2021-05-17 | 2021-05-17 | Verfahren zum analysieren einer basensequenz und genanalysator |
PCT/JP2021/018618 WO2022244058A1 (ja) | 2021-05-17 | 2021-05-17 | 塩基配列の解析方法及び遺伝子解析装置 |
CN202180095722.8A CN117043356A (zh) | 2021-05-17 | 2021-05-17 | 碱基序列的解析方法以及基因解析装置 |
JP2023522007A JPWO2022244058A1 (ja) | 2021-05-17 | 2021-05-17 | |
GB2316050.0A GB2620335A (en) | 2021-05-17 | 2021-05-17 | Method for analyzing base sequences and gene analyzer |
US18/555,972 US20240132951A1 (en) | 2021-05-17 | 2021-05-17 | Analysis method of base sequence and gene analyzer |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
PCT/JP2021/018618 WO2022244058A1 (ja) | 2021-05-17 | 2021-05-17 | 塩基配列の解析方法及び遺伝子解析装置 |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2022244058A1 true WO2022244058A1 (ja) | 2022-11-24 |
Family
ID=84141375
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/JP2021/018618 WO2022244058A1 (ja) | 2021-05-17 | 2021-05-17 | 塩基配列の解析方法及び遺伝子解析装置 |
Country Status (6)
Country | Link |
---|---|
US (1) | US20240132951A1 (ja) |
JP (1) | JPWO2022244058A1 (ja) |
CN (1) | CN117043356A (ja) |
DE (1) | DE112021007137T5 (ja) |
GB (1) | GB2620335A (ja) |
WO (1) | WO2022244058A1 (ja) |
Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2017130349A1 (ja) * | 2016-01-28 | 2017-08-03 | 株式会社日立ハイテクノロジーズ | 塩基配列決定装置、キャピラリアレイ電気泳動装置及び方法 |
US20170235874A1 (en) * | 2014-08-15 | 2017-08-17 | Life Technologies Corporation | Methods and systems for detecting minor variants in a sample of genetic material |
WO2020179405A1 (ja) * | 2019-03-05 | 2020-09-10 | 株式会社日立ハイテク | 遺伝子型解析装置及び方法 |
-
2021
- 2021-05-17 DE DE112021007137.8T patent/DE112021007137T5/de active Pending
- 2021-05-17 WO PCT/JP2021/018618 patent/WO2022244058A1/ja active Application Filing
- 2021-05-17 GB GB2316050.0A patent/GB2620335A/en active Pending
- 2021-05-17 US US18/555,972 patent/US20240132951A1/en active Pending
- 2021-05-17 JP JP2023522007A patent/JPWO2022244058A1/ja active Pending
- 2021-05-17 CN CN202180095722.8A patent/CN117043356A/zh active Pending
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20170235874A1 (en) * | 2014-08-15 | 2017-08-17 | Life Technologies Corporation | Methods and systems for detecting minor variants in a sample of genetic material |
WO2017130349A1 (ja) * | 2016-01-28 | 2017-08-03 | 株式会社日立ハイテクノロジーズ | 塩基配列決定装置、キャピラリアレイ電気泳動装置及び方法 |
WO2020179405A1 (ja) * | 2019-03-05 | 2020-09-10 | 株式会社日立ハイテク | 遺伝子型解析装置及び方法 |
Also Published As
Publication number | Publication date |
---|---|
CN117043356A (zh) | 2023-11-10 |
GB202316050D0 (en) | 2023-12-06 |
JPWO2022244058A1 (ja) | 2022-11-24 |
DE112021007137T5 (de) | 2023-12-21 |
US20240132951A1 (en) | 2024-04-25 |
GB2620335A (en) | 2024-01-03 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
EP2937685B1 (en) | Method for genotypic analysis | |
JP4991252B2 (ja) | 電気泳動装置、及び電気泳動分析方法 | |
US20200003728A1 (en) | Automated quality control and spectral error correction for sample analysis instruments | |
EP2669669B1 (en) | Capillary unit for electrophoresis apparatus | |
CN105143469B (zh) | 核酸分析装置及使用其的核酸分析方法 | |
US20240085329A1 (en) | Analysis system and analysis method | |
CA2469197A1 (en) | Multi-capillary electrophoresis apparatus | |
WO2022244058A1 (ja) | 塩基配列の解析方法及び遺伝子解析装置 | |
JP7340095B2 (ja) | 電気泳動システム | |
WO2023195077A1 (ja) | 塩基配列の解析方法及び遺伝子解析装置 | |
CN112513618B (zh) | 生物聚合物分析方法及生物聚合物分析装置 | |
CN113439117B (zh) | 基因型解析装置及方法 | |
CN114391098B (zh) | 生物体试料分析装置、生物体试料分析方法 | |
WO2024214217A1 (ja) | 遺伝子解析装置及び遺伝子解析方法 | |
JP6514369B2 (ja) | 塩基配列決定装置、キャピラリアレイ電気泳動装置及び方法 | |
JP2000258392A (ja) | 電気泳動装置 | |
CN115380208A (zh) | 电泳装置以及分析方法 | |
WO2023139711A1 (ja) | 電気泳動システム | |
WO2023223547A1 (ja) | 電気泳動データ処理装置及び電気泳動データ処理方法 | |
WO2024111038A1 (ja) | 変異遺伝子検出方法 | |
JP7261877B2 (ja) | マルチキャピラリ電気泳動装置、及びサンプル分析方法 |
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: 21940678 Country of ref document: EP Kind code of ref document: A1 |
|
WWE | Wipo information: entry into national phase |
Ref document number: 202180095722.8 Country of ref document: CN |
|
WWE | Wipo information: entry into national phase |
Ref document number: 2023522007 Country of ref document: JP |
|
WWE | Wipo information: entry into national phase |
Ref document number: 18555972 Country of ref document: US |
|
WWE | Wipo information: entry into national phase |
Ref document number: 112021007137 Country of ref document: DE |
|
ENP | Entry into the national phase |
Ref document number: 202316050 Country of ref document: GB Kind code of ref document: A Free format text: PCT FILING DATE = 20210517 |
|
122 | Ep: pct application non-entry in european phase |
Ref document number: 21940678 Country of ref document: EP Kind code of ref document: A1 |