WO2016141516A1 - Procédé d'acquisition de séquence spécifique de la progéniture, et procédé et dispositif de détection de mutation de novo de la progéniture - Google Patents

Procédé d'acquisition de séquence spécifique de la progéniture, et procédé et dispositif de détection de mutation de novo de la progéniture Download PDF

Info

Publication number
WO2016141516A1
WO2016141516A1 PCT/CN2015/073816 CN2015073816W WO2016141516A1 WO 2016141516 A1 WO2016141516 A1 WO 2016141516A1 CN 2015073816 W CN2015073816 W CN 2015073816W WO 2016141516 A1 WO2016141516 A1 WO 2016141516A1
Authority
WO
WIPO (PCT)
Prior art keywords
sub
progeny
sequencing result
reading
read
Prior art date
Application number
PCT/CN2015/073816
Other languages
English (en)
Chinese (zh)
Inventor
孙宇辉
曹红志
仝欣
李振宇
曹丹丹
Original Assignee
深圳华大基因研究院
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 深圳华大基因研究院 filed Critical 深圳华大基因研究院
Priority to PCT/CN2015/073816 priority Critical patent/WO2016141516A1/fr
Publication of WO2016141516A1 publication Critical patent/WO2016141516A1/fr

Links

Images

Classifications

    • 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

Definitions

  • the present invention relates to the field of biological information. Specifically, the present invention relates to a method for obtaining a progeny-specific sequence, a method for detecting a new mutation in a progeny, and a device for detecting a new mutation in a progeny.
  • the present invention provides a method for obtaining a progeny-specific sequence, the method comprising: obtaining a first sequencing result and a second sequencing result, wherein the first sequencing result is a genome sequencing result of the target progeny, The second sequencing result is the genome sequencing result of the father and mother of the offspring, the first sequencing result includes a plurality of reads of length K 1 , and the second sequencing result includes a plurality of reads of length K 2 ; a first sequencing result and a read in the second sequencing result, obtaining a first sub-reading set and a second sub-reading set, the first sub-reading set being composed of a plurality of first sub-reading subsets, a first sub- The subset of reads consists of all sub-reads of length K appearing in one of the first sequencing results, and the second set of sub-reads is composed of a plurality of subsets of second sub-reads, a subset of second sub-reads Compensating for all sub-reads
  • Figure 1 illustrates the method concept.
  • Obtaining the results of genome sequencing includes sequencing library construction of at least a part of the genome sequence, and sequencing the constructed sequencing library.
  • the type and preparation method of the sequencing library can be performed according to the selected sequencing method, and the optional sequencing method is based on Sequencing platforms include, but are not limited to, CG (Complete Genomics) CGA, Illumina/Solexa, Life Technologies/Ion Torrent, and Roche 454, for the preparation of single-ended or multi-end, stranded or circular sequencing libraries based on the selected sequencing platform.
  • the father and mother of the so-called offspring refer to the biological parents of the offspring and are the source individuals of the genetic information of the offspring.
  • the genome sequencing results of the target progeny and their parents can be obtained simultaneously by co-sequencing, or can be separately sequenced.
  • a tag is introduced at the time of library construction to distinguish nucleic acids from progeny and from parents, and the constructed library is mixed on the machine. Sequencing, and then sequencing the sub-generation sequencing results and their parents' sequencing results.
  • the daughter sequencing library and its parent sequencing library are separately subjected to double-end sequencing, and the corresponding sequencing results are obtained.
  • the two sequencing results include multiple pairs of read pairs, and two pairs of read pairs.
  • the reads are from the two ends of an insert, which is usually obtained by interrupting the genome of the target individual or is a free DNA fragment, and the sequencing library is a band suitable for sequencing on a certain sequencing platform. Insert the insert of the linker.
  • the read segment corresponding to the sub-read segment refers to the read segment on which the sub-read segment appears.
  • the sub-read segment and the read segment usually do not uniquely correspond, that is, generally one sub-read segment corresponds to multiple read segments.
  • neither the first sequencing result nor the second sequencing result includes a read that meets any of the following descriptions, including N exceeding 10%, mass value below 10, being contaminated by the joint,
  • N refers to the indeterminate base in the read
  • the quality value is the value assigned to the read by the sequencing platform
  • the quality value is -10*lg(p), where p is the probability of error detection, when a certain position is read
  • the probability of error is 0.1
  • the mass value is 10
  • the junction-contaminated finger refers to the sequencing link included in the reads. Removing these reads will improve the overall quality of the reads contained in the sequencing results, and will also reduce the need for subsequent fast detection analysis of the machine memory.
  • Each sub-segment of length K appearing in a read segment indicates that each subsequence in a sequence is present, and the number of subsequences appearing in one sequence is (the length of the sequence - the length of the subsequence +1)
  • the 3 bp sub-readings appearing in the 7 bp segment AGAGAGT are AGA, GAG, AGA, GAG, and AGT, with a total of 5 (ie, 7-3+1) 3 bp sub-reads, these 5 sub-reads.
  • the segments form a subset of said sub-readers.
  • a sub-reading of length K is referred to as a Kmer.
  • the first sub-segment set and the second sub-segment set are obtained by using the read sequence in the first sequencing result and the second sequencing result, respectively, including using the first sequencing result All reads, obtaining a subset of all first sub-reading segments, all first subsets of sub-reading segments constitute the first set of sub-reading segments, and all subsets in the second sequencing result are used to obtain all subsets of second sub-reading segments, All of the second subset of sub-reading segments constitute the second set of sub-reading segments.
  • the first sub-segment set and the second sub-segment set are obtained by using the read sequence in the first sequencing result and the second sequencing result, respectively, including, from the first sequencing result, the read i Start with the jth nucleotide at one end, copy the K contiguous nucleotides of the read in the other end direction into a Kmer, and take the values in ⁇ 1, 2, ..., m-1, m ⁇ , corresponding to Each i,j takes a value in ⁇ 1,2,...,(K 1 -K), (K 1 -K+1) ⁇ to obtain the first sub-read set, i is the first sequencing
  • the number of reads in the result, m is the total number of reads included in the first sequencing result, and the acquisition of the second sub-read set is similar, from the z-th core at the end of the read w in the second sequencing result Start with glycosylation, copy the K contiguous nucleotides of the read in the other end direction to a Kmer,
  • the above process of acquiring the sub-reading segment on the machine includes inputting a read segment, and transforming each input into a fixed-length output using a hash algorithm (hashing algorithm), the output being a hash value, that is, a sub-reading segment.
  • This conversion is a compression map, where the space of the hash value is usually much smaller than the input (pre-mapped) space.
  • Converting the reads to Kmer facilitates rapid comparison and calculation of specific Kmers.
  • the memory demand is related to the number and type of kmer. If the kmer is too long, there are many types of kmer. Using machine storage analysis will take up more machine memory, and if Kmer is too short, the number of Kmer will be many.
  • the use of machine storage analysis also occupies more machine memory, the number and type of kmer is related to the length of Kmer, that is, the size of K.
  • the first sequencing result and the second sequencing result include a read length of not less than 50 bp, that is, K 1 ⁇ 50 bp, K 2 ⁇ 50 bp, and preferably, the sub-reading segment may be set.
  • the length is 19 to 31 bp, which makes the requirements for machine memory low, and enables subsequent comparative analysis to be performed quickly.
  • the progeny-specific Kmer is filtered prior to extracting the corresponding reads, including filtering out the progeny-specific Kmers having a frequency less than two.
  • the frequency of a sub-read in a set refers to the number of sub-reads in the set.
  • the following embodiments can also be used to achieve the same effect as the embodiment. After obtaining the first sub-reader set and the second sub-reader set, the Kmer whose frequency is less than 2 in each Kmer set is filtered out, so that the same can be reduced. The resulting false positives for specific reads can also reduce the time required for the next comparative run.
  • the method further comprises: after obtaining the progeny-specific sequence, filtering the progeny-specific sequence, including, based on the progeny-specific Kmer frequency, filtering out in the first sub-
  • the read segment has a read set corresponding to the progeny-specific sub-reading segment having a frequency less than 2, and/or, filtering out the number of sub-specific sub-reading segments occurring thereon that have fewer than two reads.
  • the frequency of a sub-read in a set refers to the number of sub-reads in the set.
  • Figure 2 illustrates the flow of obtaining and filtering progeny-specific reads.
  • the Kmer count can be directly used by the hash table.
  • the hash table is a data structure that exchanges space for time.
  • the first sequencing result is built into a hash table.
  • the key in the hash table is Kmers, and the stored value is stored.
  • the read-out refers to the reading of the number of progeny-specific sub-readings that appear on the sub-readings that are less than 2, and if the number of progeny-specific Kmers present in a reading is less than 2, it is filtered out, for example If a 2 seed-specific Kmer appears on a progeny-specific sequence, regardless of the frequency of each of the two specific Kmers, the progeny-specific sequence is retained; if only one species is present on a progeny-specific sequence Generation-specific Kmer, the progeny-specific Kmer appears no less than 2 times on the progeny-specific sequence, and the progeny-specific sequence is also retained. Filtration of at least one of the above-described progeny-specific sequences facilitates the reduction of obtaining false positive progeny-specific sequences, and is advantageous for obtaining high-quality progeny-specific sequences.
  • the storage medium may include a read only memory, a random access memory, a magnetic disk, or an optical disk.
  • the present invention provides a method for detecting a new mutation in a progeny, comprising: obtaining a progeny-specific sequence using the method of one or both of the above-described embodiments of the invention; Specific sequence, detecting new mutations in the progeny.
  • new generation of mutations refers to mutations that are not inherited from their parents, that is, mutations that are not carried out on their parents' genomes, that is, the genotypes of the offspring at that location are different from their fathers and their mothers, here Father or mother, referring to their biological parents.
  • obtaining the progeny-specific sequence comprises filtering out the reads corresponding to the progeny-specific sub-reads having a frequency less than 2 in the first sub-reading set.
  • the read corresponding to the progeny-specific sub-reading segment having a frequency less than 2 in the first sub-reading segment is filtered out, and the number of progeny-specific sub-reading segments appearing thereon is also filtered out. Less than 2 reads.
  • the frequency of a sub-read in a set refers to the number of sub-reads in the set.
  • the detecting a new mutation of the progeny based on a progeny-specific sequence comprises: aligning the progeny-specific sequence with a reference sequence to obtain an alignment result; For the result, the progeny new mutation is detected, and the progeny new mutation includes at least one of SNP, INDEL, and SV. Comparisons can be made using, but not limited to, Samtools, SOAP, BWA, and TeraMap software. In one embodiment of the invention, the alignment is performed using BWA and Samtools in accordance with their default parameters.
  • the reference sequence used is a known sequence and may be any reference template in the biological category to which the target individual belongs in advance.
  • the reference sequence may select HG19 provided by the National Center for Biotechnology Information (NCBI). Detection of SNP, INDEL or SV may be selected but not limited to using the software SOAPsnp, SOAPindel, GATK and SOAPdenovo.
  • an apparatus for detecting a new mutation of a child comprising: a data input unit for inputting data; a data output unit for outputting data; and a storage unit for storing data, including a computer An executable program; a processor coupled to the data input unit, the data output unit, and the storage unit for executing the program, the executing the program comprising completing an aspect or any embodiment of the present invention All or part of the steps of the method of detecting new mutations in the progeny.
  • the so-called processor is generally responsible for computing and processing, and a part of the storage unit is memory, mainly for exchanging data.
  • the instructions and input data are temporarily stored in memory, transferred to the processor when the processor is idle, and processed by the processor to output the result to an output device such as a display or printer.
  • These results are also stored in memory before the output is completed. If the memory is insufficient, the resulting data will be read much slower. Execute the program All or part of the steps of the method of one aspect of the invention can be implemented quickly, and the memory requirements are lower than current methods.
  • the detection method/apparatus of the new mutation of the progeny of this aspect of the invention no longer relies on resequencing, but takes a different approach, and uses the Kmer to identify the progeny-specific reads, thereby performing a new generation of denova mutations based on these reads.
  • the detection method has a simple principle, which greatly reduces the negative effects of high heterozygosity, high mutation and high repetition area, and the accuracy and sensitivity of the detection result are high.
  • FIG. 1 is a schematic view showing the technical principle of a method for detecting a new mutation of a progeny in an embodiment of the present invention.
  • FIG. 2 is a flow diagram of the process of acquiring and filtering progeny-specific reads in one embodiment of the present invention.
  • FIG. 3 is a schematic diagram showing the frequency distribution of a child Kmer in one embodiment of the present invention.
  • FIG. 4 is a schematic diagram showing the frequency distribution of a parent Kmer in one embodiment of the present invention.
  • FIG. 5 is a schematic diagram showing the frequency distribution of the progeny-specific Kmer in the progeny Kmer set in one embodiment of the present invention, wherein the three strip columns corresponding to each frequency are 21mer and 25mer from left to right. And 29mer.
  • Figure 6 is a graph showing the relationship between the frequency of the progeny-specific Kmer and the detection sensitivity in one embodiment of the present invention.
  • Figure 7 is a graphical representation of the relationship between specific filtration conditions and detection sensitivity of progeny-specific reads of the present invention.
  • SNPs single base mutations
  • INDEL base deletions or insertions
  • SV large chromosome structural variations
  • the classification of mutations is a relative concept, in the present invention Variation or The mutation, the nucleic acid variation, the genetic variation, the chromosomal variation and the like are common, and the SNP, the indel and the SV in the present invention are generally defined, but the size of the latter two is not particularly limited in the present invention, and thus the different kinds of mutations
  • the cross-over of the size of these types of variations does not prevent one of ordinary skill in the art from performing the methods and/or apparatus of the invention described above, and achieve the results described.
  • a branch of variation which is different from an inherited mutation, that is, it is inconsistent with the genetic information of the parent, mainly because the fertilized egg changes before the division.
  • the DNA fragments are sequenced, and the sequenced objects are all a physically continuous DNA sequence called an insert, the length of which is called the insert size.
  • the insert or at least a part of the sequence of the base is read.
  • the base sequence on both sides of the insert is read from the edge to the inside, and the reading is measured.
  • the sequence is called "reads" and its length can be called read length.
  • the ratio of the total Kmer number to the total number of bases is (L - K + 1) / L, and in the above assumption, the ratio is 0.84. Due to the inevitable sequencing errors, there are often many low-frequency Kmers. The total class of these low-frequency Kmers is related to the sequencing error rate.
  • the base error rate is 0.1%
  • the Kmer size 25
  • the genome size is 3G
  • the genome sequencing depth is 50X.
  • the number of new Kmers due to the wrong base is about 3.5G
  • the number of non-repetitive 25Kmers for the human genome is about 2.5G, so that the wrong base causes the memory to increase to 2.4. Times. So in assembly, for example, before building a contig, the low frequency Kmer can be deleted or corrected.
  • the reagents, instruments, or software involved in the following examples are conventional commercial products or open source, such as purchasing a sequencing library preparation kit from Illumina, and building a library according to the kit instructions.
  • Autism is a serious widespread developmental disorder that occurs in infants and young children. Its main characteristics are social communication disorders, language communication skills, and repeated stereotyped behavior and narrow interest.
  • Family studies and twin studies have suggested that the disease has a genetic predisposition. It is a highly genetically related disease with a genetic correlation between 40% and 90%. The agreement between identical twins was 82%, and the agreement between fraternal twins was 10%.
  • the types of genomic variants associated with autism have been found to include SNPs, INDELs, and SVs, but the genetic interpretation of autism is still only about 10-20%. With the corresponding research on astronomical genomics and the application of genome-wide sequencing technology, more and more new genetic related sites have been discovered by researchers, and the degree of interpretation of genetic susceptibility of autism can be It is about 50%.
  • Illumina Hiseq2000 was used to perform routine database construction and high-depth whole-genome sequencing of the three samples, and double-end sequencing, the obtained parental and parental sequencing data were both 90G (sampling depth of about 30X each).
  • the obtained parental and parental sequencing data were both 90G (sampling depth of about 30X each).
  • the previous research results of the family Yong-hui Jiang, et al. 2013. Detection of Clinically Relevant Genetic Variants in Autism Spectrum Disorder by Whole-Genome Sequencing
  • Denovo mutation was used as the final sensitivity test.
  • Jellyfish count/dev/fd/0-m 21-s 3G-Ct 8-Q T--bf-size 10G the meaning of each parameter and the usage of Jellyfish refer to http://www .cbcb.umd.edu/software/jellyfish/.
  • the Kmer analysis requirement for a single individual is 50G and the calculation time is 12 hours.
  • Our Kmer analysis uses the third-order Kmer lengths—21 bp, 25 bp, and 29 bp—that corresponds to 21 mer, 25 mer, and 29 mer.
  • Figures 3 and 4 show the distribution of Kmer frequencies for the offspring and their parents, respectively, of which “21mer-Q "Represents the frequency distribution curve of the 21mer based on the read after the previous step. From the frequency distribution curve of Kmer of the same length, that is, from the "21mer” and “21mer-Q" curves, it can be seen that at lower depths, such as less than 5X, but with higher frequency Kmer, these Kmers are likely due to Sequencing errors include low quality reads.
  • Figure 6 shows the relationship between the minimum frequency of the progeny-specific Kmer and the sensitivity, wherein the horizontal scale represents the frequency of the progeny-specific Kmer, the ordinate represents the ratio of false negative (FN), and the lower the false negative FN value, the higher the sensitivity. It can be seen from the figure that the Kmer of three lengths has better sensitivity in the frequency range of 1-2. As the minimum frequency increases, the false negative FN values increase to different degrees, and the sensitivity decreases to some extent.
  • each specific reading generally contains a different number of specific Kmers, in order to objectively reflect the sensitivity and accuracy of the method detection, we also use a unique double gradient test, which is based on the specific Kmer frequency and each Specific reads contain the number of specific Kmers, filter specific reads, and then compare the specific reads set under different filter parameters to the reference genome detection denovo mutation, compared with 60 validated variants.
  • the sensitivity results are shown in Figure 7.
  • Figure 7 shows the relationship between the filter conditions of the progeny-specific reads and the detection sensitivity.
  • the filter conditions for the progeny-specific reads include: the frequency of the progeny-specific Kmer (frequency, which is simply expressed as freq) and specific for each progeny.
  • Sexual reads contain the number of specific Kmers.
  • the method has the following advantages: the principle is simple, and the negative effects of high heterozygosity, high mutation and high repetition area are greatly reduced; the detection sensitivity can reach nearly 100%, that is, the false negative is close to zero.

Landscapes

  • Chemical & Material Sciences (AREA)
  • Organic Chemistry (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Zoology (AREA)
  • Wood Science & Technology (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Health & Medical Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Microbiology (AREA)
  • Immunology (AREA)
  • Physics & Mathematics (AREA)
  • Molecular Biology (AREA)
  • Biotechnology (AREA)
  • Biophysics (AREA)
  • Analytical Chemistry (AREA)
  • Biochemistry (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Health & Medical Sciences (AREA)
  • Genetics & Genomics (AREA)
  • Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)

Abstract

L'invention concerne un procédé d'acquisition d'une séquence spécifique de la progéniture. Le procédé comprend : l'acquisition d'un premier résultat de séquençage et d'un second résultat de séquençage, le premier résultat de séquençage étant un résultat de séquençage de génome d'une progéniture et le second résultat de séquençage étant un résultat de séquençage de génome d'un parent de la progéniture; l'acquisition d'un premier ensemble de sous-lectures en utilisant les lectures dans le premier résultat de séquençage et l'acquisition d'un second ensemble de sous-lectures en utilisant le second résultat de séquençage, le premier ensemble de sous-lectures étant constitué de multiples premiers sous-ensembles de sous-lectures, le second ensemble de sous-lectures étant constitué de multiples seconds sous-ensembles de sous-lectures, chaque premier sous-ensemble de sous-lectures est formé par toutes les sous-lectures qui surviennent dans une lecture dans le premier résultat de séquençage et qui ont chacune une longueur de K, et chaque second sous-ensemble de sous-lectures est formé par toutes les sous-lectures qui surviennent dans une lecture dans le second résultat de séquençage et qui ont chacune une longueur de K ; la comparaison des sous-lectures dans le premier ensemble de sous-lectures et le second ensemble de sous-lectures, et l'acquisition de sous-lectures qui ne sont comprises que dans le premier ensemble de sous-lectures, les sous-lectures qui ne sont comprises que dans le premier ensemble de sous-lectures sont appelées sous-lectures spécifiques de la progéniture ; et l'extraction de lectures correspondant aux sous-lectures spécifiques de la progéniture du premier résultat de séquençage, les lectures extraites étant des séquences spécifiques de la progéniture. L'invention concerne également un procédé et un dispositif de détection d'une mutation de novo d'une progéniture.
PCT/CN2015/073816 2015-03-06 2015-03-06 Procédé d'acquisition de séquence spécifique de la progéniture, et procédé et dispositif de détection de mutation de novo de la progéniture WO2016141516A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
PCT/CN2015/073816 WO2016141516A1 (fr) 2015-03-06 2015-03-06 Procédé d'acquisition de séquence spécifique de la progéniture, et procédé et dispositif de détection de mutation de novo de la progéniture

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2015/073816 WO2016141516A1 (fr) 2015-03-06 2015-03-06 Procédé d'acquisition de séquence spécifique de la progéniture, et procédé et dispositif de détection de mutation de novo de la progéniture

Publications (1)

Publication Number Publication Date
WO2016141516A1 true WO2016141516A1 (fr) 2016-09-15

Family

ID=56878532

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2015/073816 WO2016141516A1 (fr) 2015-03-06 2015-03-06 Procédé d'acquisition de séquence spécifique de la progéniture, et procédé et dispositif de détection de mutation de novo de la progéniture

Country Status (1)

Country Link
WO (1) WO2016141516A1 (fr)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113628681A (zh) * 2021-07-21 2021-11-09 哈尔滨星云医学检验所有限公司 一种基于家系denovo突变的分析方法及其应用

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2013177581A2 (fr) * 2012-05-24 2013-11-28 University Of Washington Through Its Center For Commercialization Séquençage du génome complet d'un fœtus humain
WO2014019267A1 (fr) * 2012-08-01 2014-02-06 Bgi Shenzhen Méthode et système pour déterminer des biomarqueurs associés à une condition anormale
CN103824001A (zh) * 2014-02-27 2014-05-28 北京诺禾致源生物信息科技有限公司 染色体的检测方法和装置
CN104160391A (zh) * 2011-09-16 2014-11-19 考利达基因组股份有限公司 确定异质样本的基因组中的变异

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104160391A (zh) * 2011-09-16 2014-11-19 考利达基因组股份有限公司 确定异质样本的基因组中的变异
WO2013177581A2 (fr) * 2012-05-24 2013-11-28 University Of Washington Through Its Center For Commercialization Séquençage du génome complet d'un fœtus humain
WO2014019267A1 (fr) * 2012-08-01 2014-02-06 Bgi Shenzhen Méthode et système pour déterminer des biomarqueurs associés à une condition anormale
CN103824001A (zh) * 2014-02-27 2014-05-28 北京诺禾致源生物信息科技有限公司 染色体的检测方法和装置

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113628681A (zh) * 2021-07-21 2021-11-09 哈尔滨星云医学检验所有限公司 一种基于家系denovo突变的分析方法及其应用

Similar Documents

Publication Publication Date Title
JP6725481B2 (ja) 母体血漿の無侵襲的出生前分子核型分析
US10081839B2 (en) System and method for cleaning noisy genetic data and determining chromosome copy number
Guo et al. Multi-perspective quality control of Illumina exome sequencing data using QC3
US10083273B2 (en) System and method for cleaning noisy genetic data and determining chromosome copy number
US20150094961A1 (en) Phasing and linking processes to identify variations in a genome
Zhou et al. Prevention, diagnosis and treatment of high‐throughput sequencing data pathologies
Datta et al. Statistical analyses of next generation sequence data: a partial overview
US20200286586A1 (en) Sequence-graph based tool for determining variation in short tandem repeat regions
WO2015043278A1 (fr) Procédé et système de mise en œuvre simultanée d'une analyse de l'haplotype de gènes cibles, et détection d'une aneuploïdie chromosomique
WO2013097048A1 (fr) Procédé et dispositif pour marquer des sites polymorphes mononucléotidiques dans un génome
KR20230117036A (ko) 게놈의 반복 영역들에서의 짧은 판독물들을 시각화하기 위한 방법들 및 시스템들
WO2016141516A1 (fr) Procédé d'acquisition de séquence spécifique de la progéniture, et procédé et dispositif de détection de mutation de novo de la progéniture
D’Agaro New advances in NGS technologies
Veeramachaneni Data Analysis in Rare Disease Diagnostics
US20160154930A1 (en) Methods for identification of individuals
Hedges Bioinformatics of Human Genetic Disease Studies
Trost et al. Wilson WL Sung, Sergio L. Pereira, Joe Whitney, Ada JS Chan, Giovanna Pellecchia, Miriam S. Reuter, Si Lok, Ryan KC Yuen, Christian R. Marshall, Daniele Merico, and Stephen W. Scherer1, 2, 5, 6
Panda et al. Bioinformatics, systems biology, and systems medicine
Sio et al. Mining polymorphic SSRs from individual genome sequences
CN117095742A (zh) 一种基于核心家系的串联重复变异分型检测装置及其应用
Burkhart A method for reference-free genome assembly quality assessment

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: 15884199

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 15884199

Country of ref document: EP

Kind code of ref document: A1