CN111370065A - Method and device for detecting cross-sample contamination rate of RNA - Google Patents
Method and device for detecting cross-sample contamination rate of RNA Download PDFInfo
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Abstract
The invention discloses a method and a device for detecting RNA cross-sample cross contamination rate, wherein the method comprises the following steps: obtaining a comparison result file between sequencing data of a sample to be detected and a reference genome; screening a housekeeping gene protein coding region which covers the polymorphic sites and has an expression level not lower than a set threshold value from the comparison result file to serve as an information extraction interval; and calculating the sample pollution rate by using the information extraction interval, the comparison result file and the genetic polymorphism site information database. The method improves the defect that the software can only be used for evaluating the DNA pollution rate by screening the stably expressed polymorphic sites as the input of the pollution rate calculation software, has convenient program operation, high analysis speed, high automation degree, high reliability of analysis results compared with standard products, realizes the quality evaluation of RNA samples, and is beneficial to the accuracy of subsequent analysis.
Description
Technical Field
The invention relates to the field of cross-sample cross-contamination rate detection, in particular to a method and a device for detecting cross-sample cross-contamination rate of RNA.
Background
The gene expression profile of a tumor sample is a powerful biomarker for identifying prognosis and prediction. To date, transcript profiling has been performed on a large number of cancer frozen tissue samples, but formalin-fixed paraffin-embedded tissue (FFPE) has become a more widely used biomaterial in the medical field because fresh frozen tissue from tumor samples of long-term follow-up clinical patients is not easily collected and stored. Genome-wide gene expression profiling of tumor samples is essential for cancer research and also facilitates extensive retrospective clinical genomic studies. However, FFPE requires fixation, paraffin embedding, sectioning, staining, and other steps to avoid degradation of cellular tissues, and contamination is often present during the above-described flaking operations, as well as during transportation, storage, and manual experimental operations. There are three main aspects of contamination: across individuals, within individuals, and across species.
Currently, RNA sample pollution rate evaluation can only realize cross-species pollution evaluation basically, and the main method is as follows: the contamination fraction of other non-human species, such as microorganisms, plants, viruses, etc., is calculated by aligning sequences that cannot be aligned to the reference genome to the NCBI database. Regarding the pollution assessment mode across individuals, only the assessment mode of the DNA sample pollution rate is disclosed in the prior art, and the specific process is as follows: the method comprises the steps of adopting GATK software Contest to calculate cross contamination in human DNA second-generation sequencing data through single nucleotide polymorphic site information, providing genotype information (http:// www.1000genomes.org) of a sequencing sample, population frequency information (Contest to provide) and a comparison file of the sequencing sample, calculating the contamination level of the posterior probability by using a Bayesian method, and determining the contamination level estimated by the maximum posterior probability. The software is mainly used for detecting the DNA pollution rate, and the applicant researches and discovers that when the software is used for detecting the RNA pollution rate, the final pollution rate is extremely inaccurate due to the fact that the RNA has the problem of inconsistent expression quantity. That is, when detecting the cross contamination rate of RNA across samples, the expression levels of different samples and different genes are different in different time spaces, which may seriously affect the coverage of sequencing data of single nucleotide polymorphic sites, and further affect the evaluation of the contamination rate, so that the final evaluation result is extremely inaccurate.
Because even a small degree of cross-contamination between individual RNAs in human samples can lead to false positives in analysis results, particularly in the study of RNA samples from tumor and normal tissues, the RNA cross-contamination between individual RNAs in human samples needs to be strictly controlled. However, currently, no relevant software or process is available to achieve accurate assessment of cross-contamination of RNA across individuals.
Disclosure of Invention
Therefore, the technical problem to be solved by the present invention is to overcome the defect that there is no method and apparatus for accurately evaluating cross-individual RNA cross-contamination in the prior art, and the present invention provides a method and apparatus for more accurately evaluating cross-sample RNA cross-contamination rate.
A method of detecting a cross-sample cross-contamination rate of RNA, comprising:
obtaining a comparison result file between sequencing data of a sample to be detected and a reference genome;
screening a housekeeping gene protein coding region which covers the polymorphic sites and has an expression level not lower than a set threshold value from the comparison result file to serve as an information extraction interval;
and calculating the sample pollution rate by using the information extraction interval, the comparison result file and the genetic polymorphism site information database.
The step of screening the information extraction intervals comprises the following steps:
selecting a housekeeping gene protein coding region in a housekeeping gene database; then screening all housekeeping gene protein coding regions containing the polymorphic sites according to the coordinate information of the polymorphic sites in the genome; the polymorphic sites contained in the protein coding region of the housekeeping gene are marked as polymorphic sites Q;
calculating the expression quantity of the genes in the comparison result file, selecting the genes M of which the expression quantity is not lower than a set threshold value, selecting the polymorphic sites P falling into the genes M from the polymorphic sites Q, and taking the housekeeping gene protein coding region covering the polymorphic sites P as an information extraction interval. The gene M is preferably a housekeeping gene with an expression level not lower than a set threshold value.
The coding regions and the number of the coding regions of the housekeeping gene protein selected from the housekeeping gene database can be adjusted according to whether polymorphic sites can be searched in the housekeeping genes by different samples, and if the polymorphic sites cannot be searched, the coding regions of the housekeeping gene protein are replaced or the number of the coding regions is increased. The smaller the number, the faster the running speed, but the smaller the number, the more likely the polymorphic site will not be found finally, and the accuracy decreases, and the larger the number, the higher the accuracy but the slower the running speed. In theory, 1-3800 can meet the requirements of the present invention, and in order to obtain higher accuracy, it is preferable to perform the subsequent analysis on 2000-3800 housekeeping genes obtained from the housekeeping gene database.
After the comparison result file is obtained, the data volume of the comparison result file can be reduced by a down-sampling method. Through the reduction of the data volume, the flow operation speed is improved, and the memory loss is reduced.
The down-sampling method comprises the following steps: extracting sequencing reads of a housekeeping gene protein coding region covering the polymorphic sites from the comparison result file by adopting Samtools software; or using Picard software to compare and randomly sample the result file to obtain a sequencing read which is randomly extracted.
The pollution rate calculation software is Contest software or Conta software; wherein, a filter _ reads _ with _ N _ cigar parameter is adopted in the calculation process of the Contest software to filter sequencing reads containing unidentifiable bases; the sensitivity of detection is adjusted by the-min _ maf parameter during the calculation process of the Conta software.
When the pollution rate calculation software is Contest software, calculating the width of a pollution rate confidence interval with 95% confidence; when the contamination rate calculation software is the contin software, the RNA cross-sample cross-contamination rate when min _ maf is 0.05 is calculated.
The sample to be detected is a contaminated RNA sample mixed by cells of different individuals.
An apparatus for detecting the rate of cross-contamination of RNA across a sample, comprising:
the detection module is used for acquiring a comparison result file between sequencing data of a sample to be detected and a reference genome, and screening a housekeeping gene protein coding region which covers polymorphic sites and has an expression level not lower than a set threshold value from the comparison result file as an information extraction interval;
and the pollution rate calculation module is used for calculating the sample pollution rate through the information extraction interval, the comparison result file and the genetic polymorphism site information database.
The detection module comprises:
the data comparison module is used for comparing the sequencing data of the sample to be detected with the reference genome to obtain a comparison result file;
a coding region identification module for selecting a housekeeping gene protein coding region from a housekeeping gene database;
the polymorphic site identification module is used for screening all housekeeping gene protein coding regions containing polymorphic sites according to the coordinate information of the polymorphic sites in a genome; the polymorphic sites contained in the protein coding region of the housekeeping gene are marked as polymorphic sites Q;
and the screening module is used for obtaining the expression quantity of the genes in the comparison result file, selecting the genes M of which the expression quantity is not lower than a set threshold value, then selecting the polymorphic sites P falling into the genes M from the polymorphic sites Q, and adopting the housekeeping gene protein coding region covering the polymorphic sites P as an information extraction interval. The gene M is a housekeeping gene.
The detection module also comprises a down-sampling module which is used for reducing the data volume of the analysis sample in the comparison result file.
The technical scheme of the invention has the following advantages:
1. the method for detecting the RNA cross-sample cross-contamination rate can effectively calculate the contamination ratio of other population samples which are not the sample, and fills the blank of the RNA cross-sample cross-contamination rate evaluation method.
Meanwhile, the housekeeping gene in the present invention is also called housekeeping gene, and refers to a gene that is stably expressed in all cells, and the product thereof is necessary for maintaining the basic life activities of the cells. The applicant researches and discovers that the final pollution rate evaluation is extremely inaccurate because the sequencing reading length coverage of polymorphic sites is seriously influenced by the RNA expression quantity in the process of calculating the RNA cross-sample cross-contamination rate, and creatively selects a stably expressed housekeeping gene as a target gene for evaluating the RNA cross-sample cross-contamination rate to solve the problem. The method specifically comprises the following steps: according to the method, the housekeeping gene protein coding region covering the polymorphic sites is screened from the comparison result file to serve as the information extraction interval, and the sample pollution rate is calculated according to the selected information extraction interval, so that the influence of different gene expression quantity differences of different samples on the pollution rate analysis result can be effectively reduced, and the evaluation accuracy is improved; and the results obtained by detection are compared with the standard substance by the method in the embodiment for further verification to obtain: the average error of the method for the pollution rate estimation result is only 0.16%, and the reliability of the analysis result is high; therefore, the method can better realize the quality evaluation of the RNA sample and is beneficial to the accuracy of subsequent analysis.
In addition, the invention improves the defect that the software can only be used for evaluating the DNA pollution rate by screening the stably expressed housekeeping gene protein coding region containing the polymorphic sites as the input file of the pollution rate calculation software (such as Contest, Conta and the like), can more simply, conveniently and rapidly realize the estimation of the RNA cross-sample cross-contamination rate, and has convenient program operation, high analysis speed and high automation degree.
2. The invention reduces the data volume of the analysis sample by down-sampling, and further improves the program operation efficiency on the premise of ensuring the detection efficiency.
Detailed Description
Example 1
A method of detecting a cross-sample cross-contamination rate of RNA, comprising:
(1) providing RNA sample sequencing data of two different individuals, and comparing the RNA sample sequencing data with a ginseng reference genome (GRCH37) by using a BWA-MEM algorithm to obtain a comparison result file; the human reference genome (GRCH37) is the human genome sequence of version 37 published by NCBI. NCBI (national Center for Biotechnology information) refers to the United states national Center for Biotechnology information.
(2) And extracting comparison result files of the two different individuals according to a certain proportion, and mixing to obtain three simulated samples of cross-sample pollution gradients, wherein the real pollution rates are 1%, 3% and 5% respectively.
(3) In order to improve the program operation efficiency, the comparison result of the three simulation samples is firstly subjected to down-sampling processing. In this embodiment, the result file is randomly sampled by using Picard software for comparison, so as to obtain a sequencing read which is randomly extracted.
(4) Stably expressed housekeeping genes were selected as target genes for assessing the rate of RNA cross-sample cross-contamination. In this embodiment, the following websites are used: http:// www.tau.ac.il/. about eliis/HKG/. 3458 housekeeping genes were randomly downloaded as target genes.
(5) And traversing the gene interval of each housekeeping gene serving as the target gene in the steps in sequence by adopting programming, searching an NCBI database once for each gene interval, and finding a protein coding region in the gene interval. Because protein coding regions corresponding to different transcripts of the same gene overlap with each other, the overlapping protein coding regions on the same chromosome are combined according to coordinate information, and finally, the size of the obtained protein coding region containing 36521 integrated protein coding regions is 744 KB.
(6) All housekeeping gene protein coding regions containing polymorphic sites were selected from the protein coding region in the following manner: searching a human genome haplotype map database, namely a HapMap database, and screening according to the coordinate information of the polymorphic sites in the genome, in this embodiment, 459 housekeeping gene protein coding regions covering the polymorphic sites are screened from the protein coding regions obtained in the step (5), and as shown in table 1, the housekeeping gene protein coding regions cover 4326 polymorphic sites Q.
TABLE 1
(7) And (3) calculating the expression quantity of the housekeeping genes containing polymorphic sites in the three down-sampled simulation samples in the step (3) by using transcriptome expression quantity calculation software StringTie, filtering out the housekeeping genes with the expression quantity of 0 in any simulation sample, and taking the protein coding region of the housekeeping genes with the expression quantity of not zero in all the simulation samples as an information extraction interval.
The screening method of the information extraction interval in the step comprises the following steps: selecting a gene M with the expression quantity not lower than a set threshold value, selecting a polymorphic site P falling in the gene M from the polymorphic sites Q, and using a housekeeping gene protein coding region covering the polymorphic site P as an information extraction interval. The gene M can be all genes of which the expression quantity is not lower than a set threshold value in the simulation sample, and can also be housekeeping genes of which the expression quantity is not lower than the set threshold value in the simulation sample.
The method can screen out the information extraction interval suitable for a single simulation sample, and can also screen out the information extraction interval common to all simulation samples. When an information extraction interval suitable for a single simulation sample is screened, a gene with zero expression level is filtered from each simulation sample to obtain a gene M, then polymorphic sites Q and the gene M of each simulation sample are adopted to be respectively contrasted to obtain polymorphic sites P falling into the gene M, and finally a housekeeping gene protein coding region which covers the polymorphic sites P and has the expression level not lower than 0 in each simulation sample is respectively obtained and used as an information extraction interval corresponding to the corresponding simulation sample. When the information extraction interval common to all the simulation samples is screened out: and simultaneously filtering genes with zero expression quantity by adopting all the simulation samples to obtain genes M with the expression quantity more than zero shared by all the simulation samples, then contrasting polymorphic sites Q and the genes M shared by all the simulation samples to obtain polymorphic sites P falling into the genes M, and finally screening out information extraction intervals shared by all the simulation samples.
In this embodiment, a method of screening an information extraction interval common to all the mock samples, that is, a method of comparing three mock samples after filtration with 4326 polymorphic sites Q obtained in step (6) at the same time, is adopted. The method specifically comprises the following steps: screening out housekeeping genes M with expression quantities larger than zero in three simulation samples, selecting polymorphic sites P falling into the housekeeping genes M from the polymorphic sites Q, and taking the finally screened housekeeping gene protein coding regions with the polymorphic sites P as information extraction intervals for calculating the cross contamination rate of RNA across samples. In the embodiment, 16 information extraction intervals are screened out from the three simulation samples, which is specifically shown in table 2.
TABLE 2
| Chromosome | Starting point | Terminal point |
| 1 | 15986363 | 15988217 |
| 1 | 52498368 | 52499433 |
| 4 | 165118158 | 165118863 |
| 6 | 30297094 | 30297547 |
| 6 | 30679650 | 30681131 |
| 8 | 67341366 | 67342464 |
| 8 | 104427218 | 104427744 |
| 11 | 11373490 | 11374666 |
| 13 | 28009811 | 28010030 |
| 13 | 52602940 | 52605241 |
| 19 | 10224308 | 10225414 |
| 19 | 42582758 | 42585449 |
| 19 | 50411495 | 50413064 |
| 19 | 52393870 | 52395150 |
| 22 | 19951088 | 19951282 |
| 22 | 50962039 | 50962840 |
(8) Calculating the pollution rate by using an individual cross-contamination rate calculation tool Contest of the GATK, wherein the information extraction interval obtained in the step, the comparison result file after down-sampling and a HapMap database for providing genetic polymorphism site information are used as input; in the invention, the pollution rate can be obtained by inputting the information extraction interval of a single simulation sample, the comparison result file of the corresponding simulation sample and the HapMap database; the pollution rate can also be obtained by inputting a comparison result file of the common information extraction interval of the plurality of simulation samples and the simulation samples and a HapMap database. In this embodiment, the information extraction section corresponds to genotype information of DNA sequencing, the HapMap database corresponds to population frequency information of DNA sequencing, and the comparison result file after downsampling corresponds to a comparison file of sequencing samples. Firstly, an index is established for a comparison result file after down-sampling, and then, the calculation is carried out by applying Contest software. The- -filter _ reads _ with _ N _ cigar parameter was used in the calculation to filter sequencing reads containing unrecognized bases. In the output file, name indicates the sample name, registration indicates the sample contamination rate, confidence _ interval _95_ width indicates the confidence interval width at 95% confidence, confidence _ interval _95_ low indicates the confidence interval lower limit at 95% confidence, and confidence _ interval _95_ high indicates the confidence interval upper limit at 95% confidence.
The BWA-MEM algorithm, the Picard software, the StringTie calculation software, and the content software involved in the above steps in the present invention are all prior arts, and the specific operations are common knowledge of those skilled in the art, and therefore, the present invention is not described in detail.
(9) Performance verification
In order to verify the accuracy of the pollution rate calculation process, the pollution rate calculation of the simulated sample shows that the detection error is 0.07% at the pollution rate level of the 1% sample, 0.01% at the pollution rate level of the 3% sample and 0.40% at the pollution rate level of the 5% sample. The average error of the three gradient simulation samples is only 0.16%, and the specific detection results are shown in table 3.
TABLE 3
| Simulation sample | Sample contamination rate | The result of the detection |
| mix_01 | 1％ | 1.0744％ |
| mix_03 | 3％ | 3.0144％ |
| mix_05 | 5％ | 5.3974％ |
From the above results, it can be seen that: the average error of the estimation result of the RNA cross-sample cross-contamination rate is only 0.16%, and the reliability of the analysis result is high; therefore, the method can better realize the quality evaluation of the RNA sample and is beneficial to the accuracy of subsequent analysis.
Example 2
The difference between this embodiment and embodiment 1 is that the contamination rate values of different simulation contamination rate samples are calculated by using the Conta software in this embodiment. This example uses steps (1) to (7) which are identical to those of example 1, except that the simulation sample in this example is different, and the final calculation software is different. Specifically, in this embodiment, 23 simulated RNA samples with a contamination rate of 1% -50% were used after mixing two different individuals according to different contamination gradients. In this embodiment, 459 information extraction intervals are screened out by using the 23 simulated RNA samples, the specific information extraction intervals refer to table 1, and finally, comparison result files of different simulated RNA samples, information extraction intervals and HapMap database polymorphic site information files are input into the contin software at the same time, and simulated calculation of the simulated RNA samples is performed by using different min _ maf parameter values, with the calculation results shown in table 4.
TABLE 4
As can be seen from the above examples 1 and 2: by the method, the cross-sample contamination rate of the RNAs with different gradients can be effectively evaluated. When the compa software is used, and the calculation parameter min _ maf is 0.05, the evaluation accuracy can be further improved, and the average error is 0.034.
Example 3
A device for detecting RNA cross-sample cross-contamination rate comprises a detection module and a contamination rate calculation module.
The detection module is used for obtaining a comparison result file between the sequencing data of the sample to be detected and the reference genome, and screening a housekeeping gene protein coding region which covers the polymorphic sites and has an expression level not lower than a set threshold value from the comparison result file to serve as an information extraction interval. And the pollution rate calculation module is used for calculating the sample pollution rate by adopting pollution rate calculation software through the information extraction interval, the comparison result file and the genetic polymorphism site information database.
The detection module comprises a data comparison module, a down-sampling module, a coding region identification module, a polymorphic site identification module and a screening module; the method comprises the following specific steps:
the data comparison module is used for comparing the sequencing data of the sample to be detected with the reference genome to obtain a comparison result file;
and the down-sampling module is used for reducing the data volume of the analysis sample in the comparison result file.
A coding region identification module for selecting a housekeeping gene protein coding region from a housekeeping gene database;
the polymorphic site identification module is used for screening all housekeeping gene protein coding regions containing polymorphic sites according to the coordinate information of the polymorphic sites in a genome; the polymorphic sites contained in the protein coding region of the housekeeping gene are marked as polymorphic sites Q;
and the screening module is used for obtaining the expression quantity of the genes in the comparison result file, selecting the genes M of which the expression quantity is not lower than a set threshold value, then selecting the polymorphic sites P falling into the genes M from the polymorphic sites Q, and adopting the housekeeping gene protein coding region covering the polymorphic sites P as an information extraction interval. The gene M is a housekeeping gene.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications therefrom are within the scope of the invention.
Claims (10)
1. A method of detecting a cross-sample cross-contamination rate of RNA, comprising:
obtaining a comparison result file between sequencing data of a sample to be detected and a reference genome;
screening a housekeeping gene protein coding region which covers the polymorphic sites and has an expression level not lower than a set threshold value from the comparison result file to serve as an information extraction interval;
and calculating the sample pollution rate by using the information extraction interval, the comparison result file and the genetic polymorphism site information database.
2. The method for detecting RNA cross-sample cross-contamination rate according to claim 1, wherein the step of screening the information extraction interval comprises:
selecting a housekeeping gene protein coding region in a housekeeping gene database; then screening all housekeeping gene protein coding regions containing the polymorphic sites according to the coordinate information of the polymorphic sites in the genome; the polymorphic sites contained in the protein coding region of the housekeeping gene are marked as polymorphic sites Q;
calculating the expression quantity of the genes in the comparison result file, selecting the genes M of which the expression quantity is not lower than a set threshold value, selecting the polymorphic sites P falling into the genes M from the polymorphic sites Q, and using the housekeeping gene protein coding region covering the polymorphic sites P as an information extraction interval.
3. The method for detecting RNA cross-sample cross-contamination rate according to claim 1 or 2, wherein after the comparison result file is obtained, the data volume of the comparison result file can be reduced by a down-sampling method.
4. The method for detecting RNA cross-sample cross-contamination rate of claim 3, wherein the down-sampling method is: extracting sequencing reads of a housekeeping gene protein coding region covering the polymorphic sites from the comparison result file by adopting Samtools software; or using Picard software to compare and randomly sample the result file to obtain a sequencing read which is randomly extracted.
5. The method for detecting RNA cross-sample cross-contamination rate according to any one of claims 1 to 4, wherein the contamination rate calculation software is Contest software or Conta software; wherein, a filter _ reads _ with _ N _ cigar parameter is adopted in the calculation process of the Contest software to filter sequencing reads containing unidentifiable bases; the sensitivity of detection is adjusted by the-min _ maf parameter during the calculation process of the Conta software.
6. The method for detecting RNA cross-sample cross-contamination rate according to claim 5, wherein when the contamination rate calculation software is a Contest software, a contamination rate confidence interval width of 95% confidence is calculated; when the contamination rate calculation software is the contin software, the RNA cross-sample cross-contamination rate when min _ maf is 0.05 is calculated.
7. The method for detecting the cross-sample contamination rate of RNA according to any one of claims 1 to 6, wherein the sample to be detected is a contaminated RNA sample mixed with cells of different individuals.
8. An apparatus for detecting the rate of cross-contamination of RNA across a sample, comprising:
the detection module is used for acquiring a comparison result file between sequencing data of a sample to be detected and a reference genome, and screening a housekeeping gene protein coding region which covers polymorphic sites and has an expression level not lower than a set threshold value from the comparison result file as an information extraction interval;
and the pollution rate calculation module is used for calculating the sample pollution rate through the information extraction interval, the comparison result file and the genetic polymorphism site information database.
9. The apparatus of claim 8, wherein the detection module comprises:
the data comparison module is used for comparing the sequencing data of the sample to be detected with the reference genome to obtain a comparison result file;
a coding region identification module for selecting a housekeeping gene protein coding region from a housekeeping gene database;
the polymorphic site identification module is used for screening all housekeeping gene protein coding regions containing polymorphic sites according to the coordinate information of the polymorphic sites in a genome; the polymorphic sites contained in the protein coding region of the housekeeping gene are marked as polymorphic sites Q;
and the screening module is used for obtaining the expression quantity of the genes in the comparison result file, selecting the genes M of which the expression quantity is not lower than a set threshold value, then selecting the polymorphic sites P falling into the genes M from the polymorphic sites Q, and adopting the housekeeping gene protein coding region covering the polymorphic sites P as an information extraction interval.
10. The apparatus according to claim 8 or 9, wherein the detection module further comprises a down-sampling module for reducing the data amount of the analysis sample in the comparison result file.
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