ArticlePLoS computational biology2012
Confidence-based somatic mutation evaluation and prioritization.
Article in PLoS computational biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Preclinical Modeling of Pathway-Targeted Therapy of Human Lung Cancer in the Mouse.Cold Spring Harbor perspectives in medicine · 2024Review
- Using genotype array data to compare multi- and single-sample variant calls and improve variant call sets from deep coverage whole-genome sequencing data.Bioinformatics (Oxford, England) · 2017Article
- CIMT 2015: The right patient for the right therapy - Report on the 13th annual meeting of the Association for Cancer Immunotherapy.Human vaccines & immunotherapeutics · 2016Article
- Article
- Mutanome Engineered RNA Immunotherapy: Towards Patient-Centered Tumor Vaccination.Journal of immunology research · 2015Review
- An NGS Workflow Blueprint for DNA Sequencing Data and Its Application in Individualized Molecular Oncology.Cancer informatics · 2015Review
- Amplicon sequencing of colorectal cancer: variant calling in frozen and formalin-fixed samples.PloS one · 2015Article
- Toward better understanding of artifacts in variant calling from high-coverage samples.Bioinformatics (Oxford, England) · 2014Review
- Translation of genomics-guided RNA-based personalised cancer vaccines: towards the bedside.British journal of cancer · 2014Review
- Combining calls from multiple somatic mutation-callers.BMC bioinformatics · 2014Article
- Whole-exome sequencing enables rapid determination of xeroderma pigmentosum molecular etiology.PloS one · 2014Article
- Comprehensive analysis to improve the validation rate for single nucleotide variants detected by next-generation sequencing.PloS one · 2014Article
- Comparing somatic mutation-callers: beyond Venn diagrams.BMC bioinformatics · 2013Article
- Harnessing the antigenic fingerprint of each individual cancer for immunotherapy of human cancer: genomics shows a new way and its challenges.Cancer immunology, immunotherapy : CII · 2013Review
- A simple consensus approach improves somatic mutation prediction accuracy.Genome medicine · 2013Article
- HLA typing from RNA-Seq sequence reads.Genome medicine · 2012Article
Corrections and comments
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Next generation sequencing (NGS) has enabled high throughput discovery of somatic mutations. Detection depends on experimental design, lab platforms, parameters and analysis algorithms. However, NGS-based somatic mutation detection is prone to erroneous calls, with reported validation rates near 54% and congruence between algorithms less than 50%. Here, we developed an algorithm to assign a single statistic, a false discovery rate (FDR), to each somatic mutation identified by NGS. This FDR confidence value accurately discriminates true mutations from erroneous calls. Using sequencing data generated from triplicate exome profiling of C57BL/6 mice and B16-F10 melanoma cells, we used the existing algorithms GATK, SAMtools and SomaticSNiPer to identify somatic mutations. For each identified mutation, our algorithm assigned an FDR. We selected 139 mutations for validation, including 50 somatic mutations assigned a low FDR (high confidence) and 44 mutations assigned a high FDR (low confidence). All of the high confidence somatic mutations validated (50 of 50), none of the 44 low confidence somatic mutations validated, and 15 of 45 mutations with an intermediate FDR validated. Furthermore, the assignment of a single FDR to individual mutations enables statistical comparisons of lab and computation methodologies, including ROC curves and AUC metrics. Using the HiSeq 2000, single end 50 nt reads from replicates generate the highest confidence somatic mutation call set.
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