Accurately Identifying Low-Allelic Fraction Variants in Single Samples with Next-Generation Sequencing: Applications in Tumor Subclone Resolution

ABSTRACT Current methods for resolving genetically distinct subclones in tumor samples require somatic mutations to be clustered by allelic frequencies, which are determined by applying a variant calling program to next‐generation sequencing data. Such programs were developed to accurately distingui...

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Bibliographic Details
Published inHuman mutation Vol. 34; no. 10; pp. 1432 - 1438
Main Authors Stead, Lucy F., Sutton, Kate M., Taylor, Graham R., Quirke, Philip, Rabbitts, Pamela
Format Journal Article
LanguageEnglish
Published United States Blackwell Publishing Ltd 01.10.2013
Hindawi Limited
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Summary:ABSTRACT Current methods for resolving genetically distinct subclones in tumor samples require somatic mutations to be clustered by allelic frequencies, which are determined by applying a variant calling program to next‐generation sequencing data. Such programs were developed to accurately distinguish true polymorphisms and somatic mutations from the artifactual nonreference alleles introduced during library preparation and sequencing. However, numerous variant callers exist with no clear indication of the best performer for subclonal analysis, in which the accuracy of the assigned variant frequency is as important as correctly indicating whether the variant is present or not. Furthermore, sequencing depth (the number of times that a genomic position is sequenced) affects the ability to detect low‐allelic fraction variants and accurately assign their allele frequencies. We created two synthetic sequencing datasets, and sequenced real KRAS amplicons, with variants spiked in at specific ratios, to assess which caller performs best in terms of both variant detection and assignment of allelic frequencies. We also assessed the sequencing depths required to detect low‐allelic fraction variants. We found that VarScan2 performed best overall with sequencing depths of 100×, 250×, 500×, and 1,000× required to accurately identify variants present at 10%, 5%, 2.5%, and 1%, respectively. Cancers evolve, resulting in polyclonal tumours containing related, but genetically distinct, subclones. Somatic mutations that are distinct to small subclones will have a low variant frequency when DNA is extracted, and sequenced, from the tumour en masse. We have found that, overall, VarScan2 most accurately a) detects these low‐allelic fraction variants and b) assigns their true allelic frequency. A sequencing depth of at least 250x is required to identify variants that have as few as 5% variant alleles.
Bibliography:ArticleID:HUMU22365
Yorkshire Cancer Research - No. L341PG; No. L354PA
ark:/67375/WNG-X1WF1943-L
University of Leeds Fellowship awarded
istex:FAFA2829C7E880AA2D61B82FDA10292E1B7B51D2
Contract grant sponsors: Yorkshire Cancer Research (L341PG to PR, L354PA to PQ); University of Leeds Fellowship awarded to KS.
Communicated by Paolo M. Fortina
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ISSN:1059-7794
1098-1004
DOI:10.1002/humu.22365