Suppr超能文献

用于评估体细胞分类的癌细胞系滴定系列。

A cancer cell-line titration series for evaluating somatic classification.

作者信息

Denroche Robert E, Mullen Laura, Timms Lee, Beck Timothy, Yung Christina K, Stein Lincoln, McPherson John D, Brown Andrew M K

机构信息

Ontario Institute for Cancer Research, Toronto, ON, Canada.

Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada.

出版信息

BMC Res Notes. 2015 Dec 26;8:823. doi: 10.1186/s13104-015-1803-7.

Abstract

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).

摘要

背景

从肿瘤-正常样本对的DNA测序实验中准确检测体细胞单核苷酸变异以及小的插入和缺失是一项具有挑战性的任务。肿瘤样本常常被正常细胞污染,这混淆了体细胞变异的现有证据。此外,肿瘤具有异质性,因此亚克隆变异以较低的等位基因频率被观察到。我们在此展示一个细胞系滴定系列数据集,其可用于评估体细胞变异检测流程,目标是在低等位基因频率下可靠地检测真正的体细胞突变。

结果

将细胞系DNA与匹配的正常DNA按8种不同比例混合,以生成具有已知肿瘤细胞比例的样本,并在Illumina HiSeq上进行外显子组测序,深度大于300×。使用几种不同的变异检测流程处理数据,并进行验证实验,以离子激流PGM作为正交技术检测超过1500个体细胞变异候选位点。通过检查在不同细胞比例和覆盖深度下检测到的变异,我们表明表现最佳的流程在任何细胞比例下都能保持较高的精度水平。此外,我们估计随着细胞比例和覆盖度降低未检测到的真正体细胞变异的数量。

结论

我们的细胞系滴定系列数据集以及相关的验证结果对于此次评估是有效的,并将作为未来体细胞变异检测算法开发的宝贵数据集。该数据可在欧洲基因组-表型组存档库中获取,登录号为EGAS00001001016。数据访问需要通过国际癌症基因组联盟的数据访问合规办公室(ICGC DACO)进行注册。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9298/4691534/804b5b296007/13104_2015_1803_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验