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A cancer cell-line titration series for evaluating somatic classification
BACKGROUND: Accurate detection of somatic single nucleotide variants and small insertions and deletions from DNA sequencing experiments of tumour-normal pairs is a challenging task. Tumour samples are often contaminated with normal cells confounding the available evidence for the somatic variants. F...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4691534/ https://www.ncbi.nlm.nih.gov/pubmed/26708082 http://dx.doi.org/10.1186/s13104-015-1803-7 |
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author | Denroche, Robert E. Mullen, Laura Timms, Lee Beck, Timothy Yung, Christina K. Stein, Lincoln McPherson, John D. Brown, Andrew M. K. |
author_facet | Denroche, Robert E. Mullen, Laura Timms, Lee Beck, Timothy Yung, Christina K. Stein, Lincoln McPherson, John D. Brown, Andrew M. K. |
author_sort | Denroche, Robert E. |
collection | PubMed |
description | BACKGROUND: Accurate detection of somatic single nucleotide variants and small insertions and deletions from DNA sequencing experiments of tumour-normal pairs is a challenging task. Tumour samples are often contaminated with normal cells confounding the available evidence for the somatic variants. Furthermore, tumours are heterogeneous so sub-clonal variants are observed at reduced allele frequencies. We present here a cell-line titration series dataset that can be used to evaluate somatic variant calling pipelines with the goal of reliably calling true somatic mutations at low allele frequencies. RESULTS: Cell-line DNA was mixed with matched normal DNA at 8 different ratios to generate samples with known tumour cellularities, and exome sequenced on Illumina HiSeq to depths of >300×. The data was processed with several different variant calling pipelines and verification experiments were performed to assay >1500 somatic variant candidates using Ion Torrent PGM as an orthogonal technology. By examining the variants called at varying cellularities and depths of coverage, we show that the best performing pipelines are able to maintain a high level of precision at any cellularity. In addition, we estimate the number of true somatic variants undetected as cellularity and coverage decrease. CONCLUSIONS: Our cell-line titration series dataset, along with the associated verification results, was effective for this evaluation and will serve as a valuable dataset for future somatic calling algorithm development. The data is available for further analysis at the European Genome-phenome Archive under accession number EGAS00001001016. Data access requires registration through the International Cancer Genome Consortium’s Data Access Compliance Office (ICGC DACO). ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13104-015-1803-7) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4691534 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-46915342015-12-28 A cancer cell-line titration series for evaluating somatic classification Denroche, Robert E. Mullen, Laura Timms, Lee Beck, Timothy Yung, Christina K. Stein, Lincoln McPherson, John D. Brown, Andrew M. K. BMC Res Notes Research Article BACKGROUND: Accurate detection of somatic single nucleotide variants and small insertions and deletions from DNA sequencing experiments of tumour-normal pairs is a challenging task. Tumour samples are often contaminated with normal cells confounding the available evidence for the somatic variants. Furthermore, tumours are heterogeneous so sub-clonal variants are observed at reduced allele frequencies. We present here a cell-line titration series dataset that can be used to evaluate somatic variant calling pipelines with the goal of reliably calling true somatic mutations at low allele frequencies. RESULTS: Cell-line DNA was mixed with matched normal DNA at 8 different ratios to generate samples with known tumour cellularities, and exome sequenced on Illumina HiSeq to depths of >300×. The data was processed with several different variant calling pipelines and verification experiments were performed to assay >1500 somatic variant candidates using Ion Torrent PGM as an orthogonal technology. By examining the variants called at varying cellularities and depths of coverage, we show that the best performing pipelines are able to maintain a high level of precision at any cellularity. In addition, we estimate the number of true somatic variants undetected as cellularity and coverage decrease. CONCLUSIONS: Our cell-line titration series dataset, along with the associated verification results, was effective for this evaluation and will serve as a valuable dataset for future somatic calling algorithm development. The data is available for further analysis at the European Genome-phenome Archive under accession number EGAS00001001016. Data access requires registration through the International Cancer Genome Consortium’s Data Access Compliance Office (ICGC DACO). ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13104-015-1803-7) contains supplementary material, which is available to authorized users. BioMed Central 2015-12-26 /pmc/articles/PMC4691534/ /pubmed/26708082 http://dx.doi.org/10.1186/s13104-015-1803-7 Text en © Denroche et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Denroche, Robert E. Mullen, Laura Timms, Lee Beck, Timothy Yung, Christina K. Stein, Lincoln McPherson, John D. Brown, Andrew M. K. A cancer cell-line titration series for evaluating somatic classification |
title | A cancer cell-line titration series for evaluating somatic classification |
title_full | A cancer cell-line titration series for evaluating somatic classification |
title_fullStr | A cancer cell-line titration series for evaluating somatic classification |
title_full_unstemmed | A cancer cell-line titration series for evaluating somatic classification |
title_short | A cancer cell-line titration series for evaluating somatic classification |
title_sort | cancer cell-line titration series for evaluating somatic classification |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4691534/ https://www.ncbi.nlm.nih.gov/pubmed/26708082 http://dx.doi.org/10.1186/s13104-015-1803-7 |
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