Estimating genotype error rates from high-coverage next-generation sequence data.

Genome Res

Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California 94143, USA; Institute for Human Genetics, University of California San Francisco, San Francisco, California 94143, USA; Kaiser Permanente Northern California Division of Research, Oakland, California 94612, USA.

Published: November 2014

Exome and whole-genome sequencing studies are becoming increasingly common, but little is known about the accuracy of the genotype calls made by the commonly used platforms. Here we use replicate high-coverage sequencing of blood and saliva DNA samples from four European-American individuals to estimate lower bounds on the error rates of Complete Genomics and Illumina HiSeq whole-genome and whole-exome sequencing. Error rates for nonreference genotype calls range from 0.1% to 0.6%, depending on the platform and the depth of coverage. Additionally, we found (1) no difference in the error profiles or rates between blood and saliva samples; (2) Complete Genomics sequences had substantially higher error rates than Illumina sequences had; (3) error rates were higher (up to 6%) for rare or unique variants; (4) error rates generally declined with genotype quality (GQ) score, but in a nonlinear fashion for the Illumina data, likely due to loss of specificity of GQ scores greater than 60; and (5) error rates increased with increasing depth of coverage for the Illumina data. These findings, especially (3)-(5), suggest that caution should be taken in interpreting the results of next-generation sequencing-based association studies, and even more so in clinical application of this technology in the absence of validation by other more robust sequencing or genotyping methods.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4216915PMC
http://dx.doi.org/10.1101/gr.168393.113DOI Listing

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