Research Abstract


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

2013年7月8日 Scientific Reports 3 : 2161 doi: 10.1038/srep02161


重水 大智1, 藤本 明洋1, 秋山 真太郎1, 阿部 哲雄1, 中野 かおる2, Keith A. Boroevich1, 山本 裕二郎2, 古田 繭子2, 久保 充明3, 中川 英刀2 & 角田 達彦1

  1. 理化学研究所 統合生命医科学研究センター 医科学数理研究グループ
  2. 理化学研究所 統合生命医科学研究センター ゲノムシーケンス解析研究チーム
  3. 理化学研究所 統合生命医科学研究センター 基盤技術開発研究グループ
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.