CN108154007A - Number variation and deletion type detection method, computer are copied based on single tumor sample - Google Patents
Number variation and deletion type detection method, computer are copied based on single tumor sample Download PDFInfo
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- CN108154007A CN108154007A CN201711219637.XA CN201711219637A CN108154007A CN 108154007 A CN108154007 A CN 108154007A CN 201711219637 A CN201711219637 A CN 201711219637A CN 108154007 A CN108154007 A CN 108154007A
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- copy number
- number variation
- read
- deletion type
- tumor sample
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- G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
- G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
Abstract
The invention belongs to copy number variation detection technique field, it discloses a kind of based on single tumor sample copy number variation and deletion type detection method, computer, establish the homeostatic mechanisms of copy number extension and copy number Deletions range, iterative detection process constantly corrects the benchmark of read number, correct the parameter of statistical check distribution, objective detection conspicuousness copy number variation and weak significant copy number variation；Build Bayesian inference model, correct detection copy number variation state and copy number deletion type.Correct detection copy number variation state and copy number deletion type of the invention provide the information of heterozygote missing and homologous deletion.The present invention considers comparison quality and Problem-Error, has reasonably corrected full-length genome G/C content；The homeostatic mechanisms of copy number extension and copy number Deletions range are established, the benchmark of copy number is accurately positioned, the accurate change metachromatic state for detecting copy number.
Description
Technical field
The invention belongs to copy number variation detection technique field more particularly to a kind of list tumor sample that is based on to copy number variation
And deletion type detection method, computer.
Background technology
Existing expert proposes a variety of copy number mutation detection methods both at home and abroad at present, these methods are broadly divided into three types
Type：Copy number variation detection based on multiple tumor samples, wherein the first type lay particular emphasis on consistency in detection multisample and copy
Shellfish number variation pattern finds covariation pattern for same kind of cancer, and discovery and research for Disease-causing gene provide science
Foundation；The detection method of second of type and third type, which is laid particular emphasis on, carries out the genome of a certain patient copy number variation inspection
It surveys, is prediction, diagnosis, the searching of target drug of disease to observe whether Disease-causing gene or potential Disease-causing gene morph
Scientific basis is provided.In actual medical procedure, it is contemplated that the cost problem of DNA sequencing often only surveys tumor tissues
Sequence, and there is no sampled and be sequenced to nonneoplastic tissue.It is detected currently for the copy number variation of single tumor sample, but its
Detection performance is relatively low, i.e., correct verification and measurement ratio is not high and false positive is excessively high.CNVnator and readDepth methods are mainly by dividing
The otherness of full-length genome or chromosome read number is analysed, builds mathematical models, so as to detect significant copy number variation；
FREEC methods are by analyzing full-length genome G/C content, utilize deviation of the G/C content in different genes pack section
Infer extension and the miss status of copy number.These methods do not consider copy number amplification and the disequilibrium of Deletions range, from
And the distant region of copy number variation amplitude is caused to be difficult to be detected.Specifically, copy number extended amplitude can be up to from 3
It is dozens or even hundreds of, and copy number Deletions range only has 1 and 0, then corresponding sequencing read number can be in copy number extended area
Significantly difference is generated with copy number absent region, using such data structure copy number detection benchmark and examines distribution, it is past
Toward deviation can be caused, such as on the basis of the read number mean value of full-length genome, established with reference to its variance and examine distribution, then the benchmark
Often close to the smaller region of copy number amplification amplitude, shown in below figure scene, the read that is averaged number is 50, corresponding to the 2nd section
Amplification region is averaged by this on the basis of read number, then the 2nd section of region can not be detected, while other normal regions also have
It may be detected as copy number missing.On the other hand, existing most methods do not fully consider that tumour purity causes tumour
The deviation of sequencing data, i.e.,：The tumor tissues being sequenced in sequencing procedure are often containing a certain amount of normal cell, so as to make
Data observed by obtaining are the mixed signals of a tumour-normal cell, reduce read number in tumour cell and are copying
Otherness in shellfish number variation and region of not morphing, this undoubtedly increases the difficulty of copy number variation detection, and if do not had
Fully consider the problem, then the smaller region of copy number variation amplitude can not be detected.Finally, current existing majority side
Method does not account for the test problems of copy number deletion type, i.e. heterozygote missing and homologous deletion, and both missings are for life
Object function has different performances.
In conclusion problem of the existing technology is：The benchmark of genome read number is difficult to position；It is existing to be based on list
The method of tumor sample does not account for the purity problem of tumor tissues, and do not account for copying in number variation detection process is copied
The detection of shellfish number deletion type so that the accuracy of copy number variation declines, and can not provide heterozygote missing and homologous deletion
Information.
Invention content
In view of the problems of the existing technology, number variation and missing are copied based on single tumor sample the present invention provides one kind
Type detection method, computer.
The invention is realized in this way a kind of copy number variation and deletion type detection method, institute based on single tumor sample
It states and copy number extension and copy number Deletions range is established based on single tumor sample copy number variation and deletion type detection method
Homeostatic mechanisms, iterative detection process constantly correct the benchmark of read number, the parameter of corrigendum statistical check distribution, objective detection
Conspicuousness copies number variation and weak significant copy number variation；Build Bayesian inference model, correct detection copy number variation
State and copy number deletion type.
Further, it is described that number variation and deletion type detection method are copied using read number obedience pool based on single tumor sample
The property of pine distribution, calculates the probability value of each bin, establishes normal distribution according to probability value, calculates the p value of each bin, sets
Significant copy number variation has occurred in significance threshold value, the bins less than threshold value；
Significant bins is weeded out, is reused RC is balanced, again
Zero cloth is built, detects weak significant copy number variation.
Further, the structure Bayesian inference model position：
Copy number extends and missing, copy number heterozygote missing and homologous deletion state：
Prior probability estimated by significant bins probability, conditional probability p (bini∈ CNV | gain) and p (bini
∈ CNV | loss) it is calculated by the RC values observed：
Further, the data input that number variation and deletion type detection method are copied based on single tumor sample is included：
SAM files, Read.txt files and reference sequences.
Further, it is described to be copied at number variation and the read number Regularization of deletion type detection method based on single tumor sample
Reason includes：Read number after comparison, the size for setting bin is 1000, the read count (RC) of each bin is calculated, into professional etiquette
Integralization processing corrects G/C content and to the processing of being balanced of RC：
Wherein,The RC of i-th of bin observed by representing,WithRespectively represent full genome RC average values and which and
I-th of bin has the RC average values of identical G/C content bins, reRepresent RC, L_read, N_read and L_bin that mistake compares
Represent the length of read respectively, in SAM files in the number of read and full-length genome bin number, QjRepresent j-th of reading
The comparison quality of section；rmaxAnd rminRC maximum in full genome and minimum RC is represented respectively.
The present invention establishes the homeostatic mechanisms of copy number extension and copy number Deletions range, by iterative detection process not
The benchmark of disconnected corrigendum read number, the parameter of corrigendum statistical check distribution, with objective detection conspicuousness copy number variation and weak aobvious
The copy number variation of work.
The present invention fully considers tumor tissues purity and compares Problem-Error, Bayesian inference model is built, correctly to examine
Copy number variation state and copy number deletion type are surveyed, the information of heterozygote missing and homologous deletion is provided.
The present invention considers comparison quality and Problem-Error, has reasonably corrected full-length genome G/C content, and existing method exists
GC does not account for comparing quality and mistake when correcting；The present invention establishes copy number extension and the dynamic of copy number Deletions range is put down
Weighing apparatus mechanism, the benchmark of copy number is accurately positioned, the accurate change metachromatic state for detecting copy number, and existing method is mostly with full genome
Group read number mean value is difficult to the sequencing data of highly complex variation to obtain objective detection performance as benchmark.
The present invention constructs Bayesian inference model, carries out copy number amplification to significant bins and miss status pushes away
Reason；Simultaneously using tumour purity structure copy number homologous deletion conditional probability computation model, with it is objective to heterozygote missing and
Homologous deletion distinguishes.Such as in truthful data, homologous deletion is not meant to that the read number of the segment is 0, because of sequencing
The DNA of normal structure in sequencing tissue is very likely collected in the process, so that homologous deletion occurs in tumour cell,
And the read number observed is not 0；Therefore, the tumour purity that considers of the present invention is conducive to correctly distinguish heterozygote and lacks and together
Source lacks.
The present invention provides data reference for the detection of patient's personalization with treatment, provides gene more comprehensively, more rich
Group variation data understand that life mechanism, cancer cell development mechanism provide significant data support to be deep.The present invention establishes to unite
Computational methods based on meter is theoretical, build homeostatic mechanisms and Bayesian inference model, detect and are copied in single tumor sample
Number variation pattern provides foundation for doctor to the diagnosis of patient.The present invention can be in the case where lacking check sample, to sequencing
The relatively low single tumor sample of depth accurately detects copy number variation；Can detect copy number deletion type, i.e., heterozygote missing and
Homologous deletion；By the extension of dynamic equilibrium copy number and copy number Deletions range, corrigendum statistical check distributed constant (i.e. mean value with
Variance), to detect the weaker copy number variation of conspicuousness.
Description of the drawings
Fig. 1 is provided in an embodiment of the present invention based on single tumor sample copy number variation and deletion type detection method flow
Figure.
Fig. 2 is the reality provided in an embodiment of the present invention that number variation and deletion type detection method are copied based on single tumor sample
Existing flow chart.
Fig. 3 is provided in an embodiment of the present invention based on single tumor sample copy number variation and deletion type detection method method
(CONDEL) and FREEC, ReadDepth, CNVnator, CNV-seq, SeqCNV and cn.MOPS carry out performance comparison diagram.
Specific embodiment
In order to make the purpose , technical scheme and advantage of the present invention be clearer, with reference to embodiments, to the present invention
It is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not used to
Limit the present invention.
Homeostatic mechanisms and pattra leaves of copy number amplification of the present invention structure based on statistical theory with Deletions range
This inference pattern is that cancer is pre- with diversified copy number variant form and copy number deletion type in the single tumor sample of detection
It surveys, diagnose, target drug is searched and provides reliable basis.
The application principle of the present invention is explained in detail below in conjunction with the accompanying drawings.
As shown in Figure 1, provided in an embodiment of the present invention copy number variation and deletion type detection side based on single tumor sample
Method includes the following steps：
S101：The homeostatic mechanisms of copy number extension and copy number Deletions range are established, by iterative detection process not
The benchmark of disconnected corrigendum read number, the parameter of corrigendum statistical check distribution, objective detection conspicuousness copy number variation and it is weak significantly
Copy number variation；
S102：Bayesian inference model is built, number variation state and copy number deletion type are copied with correct detection, provided
Heterozygote lacks the information with homologous deletion.
The application principle of the present invention is further described below in conjunction with the accompanying drawings.
As shown in Fig. 2, provided in an embodiment of the present invention copy number variation and deletion type detection side based on single tumor sample
Method includes the following steps：
(1) data input, SAM files, Read.txt files and reference sequences.
(2) read number regularization.On the basis of input file, for the read number after comparison, set that bin's is big
Small is 1000, calculates the readcount (RC) of each bin, and design the following formula carries out regularization, i.e., G/C content carried out
It corrects and to the processing of being balanced of RC：
Wherein,The RC of i-th of bin observed by representing,WithRespectively represent full genome RC average values and which and
I-th of bin has the RC average values of identical G/C content bins, reRepresent RC, L_read, N_read and L_bin that mistake compares
Represent the length of read respectively, in SAM files in the number of read and full-length genome bin number, QjRepresent j-th of reading
The comparison quality of section.
Formula (3) is mainly used for the processing of being balanced of read number, wherein rmaxAnd rminIt represents in full genome respectively
Maximum RC and minimum RC the advantage of doing so is that potential copy number amplification and Deletions range can be balanced, is closed with building
The statistical check distribution of reason.
(3) statistical inspection model is established
It is carrying out on G/C content corrigendum and RC equilibratings processing basis, the property of Poisson distribution is obeyed using read number,
The probability value of each bin is calculated, normal distribution (i.e. zero cloth) is established, and then calculate the p value of each bin according to the probability value.
Design significance threshold value, such as 0.01,0.001 etc..Bins less than the threshold value is considered that significant copy number change has occurred
It is different.
In order to establish more true zero cloth, design iteration detection process will significantly bins weed out, recycling
Formula (3) is balanced RC, and then rebuilds zero cloth, to detect weak significant copy number variation.This dynamic equilibrium
Benefit be that the mean value of normal distribution can be moved closer to the benchmark of copy number, it is objective detection copy number variation.
(4) the copy number variation state based on bayesian theory derives
For significant bins, by building Bayesian inference model, such as formula (4) and (5), copy number is extended and is lacked
It loses, copy number heterozygote missing makes inferences with homologous deletion state：
For its Bayesian probability computational methods such as formula (6) of formula (4) and (7).Wherein prior probability can be by aobvious
The bins probability of work is estimated, and conditional probability p (bini∈ CNV | gain) and p (bini∈ CNV | loss) sight can be passed through
The RC values observed calculate.Similarly, for formula (5), same method can also be used and calculated：
In conditional probability calculating process, the present invention has fully considered tumour purity, has compared the shadow that the factors such as mistake are brought
It rings, effectively reduces copy number variation state and deletion type detection error rate.
The application effect of the present invention is explained in detail with reference to emulation.
By the method for the present invention (CONDEL) and other go together method FREEC, ReadDepth, CNVnator, CNV-seq,
SeqCNV, and cn.MOPS carry out performance comparison.Detailed process is as follows：Based on No. 21 chromosomes of mankind's reference sequences, utilize
IntSIM analogue systems simulate 14 copy number variations, and (including 6 extended areas, 4 heterozygotes lack and 4 homologous deletion areas
Domain), according to emulation different in tumour purity and sequencing overburden depth setting two, each emulation generates 50 groups of data.At this
The method of the present invention (CONDEL) and other methods in 6 of going together are tested on data set and compared with its performance, it is as shown below,
The correct recognition rata of 7 kinds of methods is portrayed using boxplot.As can be seen from Fig. 3, the method for the present invention has higher and metastable
Correct recognition rata.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all essences in the present invention
All any modification, equivalent and improvement made within refreshing and principle etc., should all be included in the protection scope of the present invention.
Claims (7)
1. one kind copies number variation and deletion type detection method based on single tumor sample, which is characterized in that described based on single swollen
Knurl sample copies number variation and deletion type detection method establishes the dynamic balance machine of copy number extension and copy number Deletions range
System, iterative detection process constantly correct the benchmark of read number, the parameter of corrigendum statistical check distribution, objective detection conspicuousness copy
Number variation and weak significant copy number variation；Build Bayesian inference model, correct detection copy number variation state and copy
Number deletion type.
2. as described in claim 1 copy number variation and deletion type detection method based on single tumor sample, which is characterized in that
It is described that the property of number variation and deletion type detection method using the obedience Poisson distribution of read number, meter are copied based on single tumor sample
The probability value of each bin is calculated, normal distribution is established according to probability value, calculates the p value of each bin, significance threshold value is set,
Significant copy number variation has occurred in bins less than threshold value；
Significant bins is weeded out, is reused RC is balanced, is rebuild
Zero cloth detects weak significant copy number variation.
3. as described in claim 1 copy number variation and deletion type detection method based on single tumor sample, which is characterized in that
The structure Bayesian inference model position：
Copy number extends and missing, copy number heterozygote missing and homologous deletion state：
Prior probability estimated by significant bins probability, conditional probability p (bini∈ CNV | gain) and p (bini∈CNV|
Loss it) is calculated by the RC values observed：
4. as described in claim 1 copy number variation and deletion type detection method based on single tumor sample, which is characterized in that
The data input that number variation and deletion type detection method are copied based on single tumor sample is included：SAM files, Read.txt
File and reference sequences.
5. as claimed in claim 4 copy number variation and deletion type detection method based on single tumor sample, which is characterized in that
The read number regularization that number variation and deletion type detection method are copied based on single tumor sample is included：After comparison
Read number, the size for setting bin is 1000, calculates the read count (RC) of each bin, carries out regularization, GC is contained
Amount is corrected and to the processing of being balanced of RC：
Wherein,The RC of i-th of bin observed by representing,WithRespectively represent full genome RC average values and which and i-th
A bin has the RC average values of identical G/C content bins, reRepresent RC, L_read, N_read and L_bin points that mistake compares
Not Biao Shi read length, in SAM files in the number of read and full-length genome bin number, QjRepresent j-th of read
Comparison quality；rmaxAnd rminRC maximum in full genome and minimum RC is represented respectively.
6. a kind of copy number variation and deletion type detection using described in 5 any one of Claims 1 to 5 based on single tumor sample
The computer program of method.
7. a kind of copy number variation and deletion type detection using described in 5 any one of Claims 1 to 5 based on single tumor sample
The computer of method.
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| CN108875302A (en) * | 2018-06-22 | 2018-11-23 | 广州漫瑞生物信息技术有限公司 | A kind of system and method for detection cell free oncogene copy number variation |
| CN110289047A (en) * | 2019-05-15 | 2019-09-27 | 西安电子科技大学 | Tumour purity and absolute copy number prediction technique and system based on sequencing data |
| CN110808084A (en) * | 2019-09-19 | 2020-02-18 | 西安电子科技大学 | Copy number variation detection method based on single-sample second-generation sequencing data |
| CN112885406A (en) * | 2020-04-16 | 2021-06-01 | 深圳裕策生物科技有限公司 | Method and system for detecting HLA heterozygosity loss |
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