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Bioinformatics DOI:10.1093/bioinformatics/btu356

Toward better understanding of artifacts in variant calling from high-coverage samples.

Publication TypeJournal Article
Year of Publication2014
AuthorsLi, H
JournalBioinformatics
Volume30
Issue20
Pages2843-51
Date Published2014 Oct 15
ISSN1367-4811
KeywordsArtifacts, Cell Line, Databases, Genetic, Genome, Human, Genomics, Genotype, Haploidy, High-Throughput Nucleotide Sequencing, Humans, INDEL Mutation, Polymorphism, Single Nucleotide
Abstract

MOTIVATION: Whole-genome high-coverage sequencing has been widely used for personal and cancer genomics as well as in various research areas. However, in the lack of an unbiased whole-genome truth set, the global error rate of variant calls and the leading causal artifacts still remain unclear even given the great efforts in the evaluation of variant calling methods.

RESULTS: We made 10 single nucleotide polymorphism and INDEL call sets with two read mappers and five variant callers, both on a haploid human genome and a diploid genome at a similar coverage. By investigating false heterozygous calls in the haploid genome, we identified the erroneous realignment in low-complexity regions and the incomplete reference genome with respect to the sample as the two major sources of errors, which press for continued improvements in these two areas. We estimated that the error rate of raw genotype calls is as high as 1 in 10-15 kb, but the error rate of post-filtered calls is reduced to 1 in 100-200 kb without significant compromise on the sensitivity.

AVAILABILITY AND IMPLEMENTATION: BWA-MEM alignment and raw variant calls are available at http://bit.ly/1g8XqRt scripts and miscellaneous data at https://github.com/lh3/varcmp.

CONTACT: hengli@broadinstitute.org

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

URLhttp://bioinformatics.oxfordjournals.org/cgi/pmidlookup?view=long&pmid=24974202
DOI10.1093/bioinformatics/btu356
Pubmed

http://www.ncbi.nlm.nih.gov/pubmed/24974202?dopt=Abstract

Alternate JournalBioinformatics
PubMed ID24974202
PubMed Central IDPMC4271055
Grant ListR01 GM100233 / GM / NIGMS NIH HHS / United States
GM100233 / GM / NIGMS NIH HHS / United States
U54HG003037 / HG / NHGRI NIH HHS / United States