ArticleBMC bioinformatics2013
Comparing somatic mutation-callers: beyond Venn diagrams.
Article in BMC bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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Who cites it
41 citing papers in PubMed.
- An alignment-free strategy for circulating tumor DNA detection and tumor fraction estimation from whole-genome sequencing data.PLoS computational biology · 2026Article
- Synth4bench: generating synthetic data for benchmarking tumor-only somatic variant calling algorithms.Frontiers in bioinformatics · 2026Article
- A Novel Affordable and Reliable Framework for Accurate Detection and Comprehensive Analysis of Somatic Mutations in Cancer.International journal of molecular sciences · 2024Article
- Cross-Site Concordance Evaluation of Tumor DNA and RNA Sequencing Platforms for the CIMAC-CIDC Network.Clinical cancer research : an official journal of the American Association for Cancer Research · 2021Article
- Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-genome sequencing.Nature biotechnology · 2021Article
- Generalizable characteristics of false-positive bacterial variant calls.Microbial genomics · 2021Article
- Repurposing RNA sequencing for discovery of RNA modifications in clinical cohorts.Science advances · 2021Article
- Precise Identification of Recurrent Somatic Mutations in Oral Cancer Through Whole-Exome Sequencing Using Multiple Mutation Calling Pipelines.Frontiers in oncology · 2021Article
- A validated lineage-derived somatic truth data set enables benchmarking in cancer genome analysis.Communications biology · 2020Article
- Accuracy and reproducibility of somatic point mutation calling in clinical-type targeted sequencing data.BMC medical genomics · 2020Article
- SomaticCombiner: improving the performance of somatic variant calling based on evaluation tests and a consensus approach.Scientific reports · 2020Article
- Reliability of Whole-Exome Sequencing for Assessing Intratumor Genetic Heterogeneity.Cell reports · 2018Article
- Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines.Cell systems · 2018Article
- Article
- Strategies for identification of somatic variants using the Ion Torrent deep targeted sequencing platform.BMC bioinformatics · 2018Article
- Informatics for cancer immunotherapy.Annals of oncology : official journal of the European Society for Medical Oncology · 2017Review
- Intersect-then-combine approach: improving the performance of somatic variant calling in whole exome sequencing data using multiple aligners and callers.Genome medicine · 2017Article
- Detailed simulation of cancer exome sequencing data reveals differences and common limitations of variant callers.BMC bioinformatics · 2017Article
- Unmasking targets of antitumor immunity via high-throughput antigen profiling.Current opinion in biotechnology · 2016Review
- In-depth comparison of somatic point mutation callers based on different tumor next-generation sequencing depth data.Scientific reports · 2016Article
Corrections and comments
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2 authors.
Funding
Abstract
backgroundSomatic mutation-calling based on DNA from matched tumor-normal patient samples is one of the key tasks carried by many cancer genome projects. One such large-scale project is The Cancer Genome Atlas (TCGA), which is now routinely compiling catalogs of somatic mutations from hundreds of paired tumor-normal DNA exome-sequence data. Nonetheless, mutation calling is still very challenging. TCGA benchmark studies revealed that even relatively recent mutation callers from major centers showed substantial discrepancies. Evaluation of the mutation callers or understanding the sources of discrepancies is not straightforward, since for most tumor studies, validation data based on independent whole-exome DNA sequencing is not available, only partial validation data for a selected (ascertained) subset of sites.
resultsTo provide guidelines to comparing outputs from multiple callers, we have analyzed two sets of mutation-calling data from the TCGA benchmark studies and their partial validation data. Various aspects of the mutation-calling outputs were explored to characterize the discrepancies in detail. To assess the performances of multiple callers, we introduce four approaches utilizing the external sequence data to varying degrees, ranging from having independent DNA-seq pairs, RNA-seq for tumor samples only, the original exome-seq pairs only, or none of those.
conclusionsOur analyses provide guidelines to visualizing and understanding the discrepancies among the outputs from multiple callers. Furthermore, applying the four evaluation approaches to the whole exome data, we illustrate the challenges and highlight the various circumstances that require extra caution in assessing the performances of multiple callers.
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