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Bioinformatics DOI:10.1093/bioinformatics/btu345

SMaSH: a benchmarking toolkit for human genome variant calling.

Publication TypeJournal Article
Year of Publication2014
AuthorsTalwalkar, A, Liptrap, J, Newcomb, J, Hartl, C, Terhorst, J, Curtis, K, Bresler, M'ayan, Song, YS, Jordan, MI, Patterson, D
JournalBioinformatics
Volume30
Issue19
Pages2787-95
Date Published2014 Oct
ISSN1367-4811
KeywordsAlgorithms, Computational Biology, Data Interpretation, Statistical, Databases, Genetic, Genome, Human, Genomics, High-Throughput Nucleotide Sequencing, Humans, INDEL Mutation, Polymorphism, Single Nucleotide, Software
Abstract

MOTIVATION: Computational methods are essential to extract actionable information from raw sequencing data, and to thus fulfill the promise of next-generation sequencing technology. Unfortunately, computational tools developed to call variants from human sequencing data disagree on many of their predictions, and current methods to evaluate accuracy and computational performance are ad hoc and incomplete. Agreement on benchmarking variant calling methods would stimulate development of genomic processing tools and facilitate communication among researchers.

RESULTS: We propose SMaSH, a benchmarking methodology for evaluating germline variant calling algorithms. We generate synthetic datasets, organize and interpret a wide range of existing benchmarking data for real genomes and propose a set of accuracy and computational performance metrics for evaluating variant calling methods on these benchmarking data. Moreover, we illustrate the utility of SMaSH to evaluate the performance of some leading single-nucleotide polymorphism, indel and structural variant calling algorithms.

AVAILABILITY AND IMPLEMENTATION: We provide free and open access online to the SMaSH tool kit, along with detailed documentation, at smash.cs.berkeley.edu

URLhttp://bioinformatics.oxfordjournals.org/cgi/pmidlookup?view=long&pmid=24894505
DOI10.1093/bioinformatics/btu345
Pubmed

http://www.ncbi.nlm.nih.gov/pubmed/24894505?dopt=Abstract

Alternate JournalBioinformatics
PubMed ID24894505
PubMed Central IDPMC4173010
Grant ListT32 HG000047 / HG / NHGRI NIH HHS / United States
T32-HG00047 / HG / NHGRI NIH HHS / United States