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. 2013:3:2161.
doi: 10.1038/srep02161.

A practical method to detect SNVs and indels from whole genome and exome sequencing data

Daichi Shigemizu  1 , Akihiro Fujimoto, Shintaro Akiyama, Tetsuo Abe, Kaoru Nakano, Keith A Boroevich, Yujiro Yamamoto, Mayuko Furuta, Michiaki Kubo, Hidewaki Nakagawa, Tatsuhiko Tsunoda
Affiliations

A practical method to detect SNVs and indels from whole genome and exome sequencing data

Daichi Shigemizu et al. Sci Rep. 2013.

Abstract

The recent development of massively parallel sequencing technology has allowed the creation of comprehensive catalogs of genetic variation. However, due to the relatively high sequencing error rate for short read sequence data, sophisticated analysis methods are required to obtain high-quality variant calls. Here, we developed a probabilistic multinomial method for the detection of single nucleotide variants (SNVs) as well as short insertions and deletions (indels) in whole genome sequencing (WGS) and whole exome sequencing (WES) data for single sample calling. Evaluation with DNA genotyping arrays revealed a concordance rate of 99.98% for WGS calls and 99.99% for WES calls. Sanger sequencing of the discordant calls determined the false positive and false negative rates for the WGS (0.0068% and 0.17%) and WES (0.0036% and 0.0084%) datasets. Furthermore, short indels were identified with high accuracy (WGS: 94.7%, WES: 97.3%). We believe our method can contribute to the greater understanding of human diseases.

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Figures

Figure 1
Figure 1. Read depth per nucleotide and GC content.
(a) Distribution of read depth in WGS and WES on-target regions. (b) Distribution of GC content of WES on-target regions.
Figure 2
Figure 2. Common indels identified by VCMM, GATK and SAMtools.
(a) SNV in WGS. SNVs in repeat regions and unknown contigs were not used for the comparison. (b) Indel in WGS. Indels in repeat regions and unknown contigs were not used for the comparison. (c) SNV in WES. (d) Coding indel in WES.
See this image and copyright information in PMC

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