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

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

doi:10.1038/srep02161

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

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

Research output: Contribution to journal › Article › peer-review

38 Citations (Scopus)

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.

Original language	English
Article number	2161
Journal	Scientific reports
Volume	3
DOIs	https://doi.org/10.1038/srep02161
Publication status	Published - 2013
Externally published	Yes

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title = "A practical method to detect SNVs and indels from whole genome and exome sequencing data",

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.",

author = "Daichi Shigemizu and Akihiro Fujimoto and Shintaro Akiyama and Tetsuo Abe and Kaoru Nakano and Boroevich, {Keith A.} and Yujiro Yamamoto and Mayuko Furuta and Michiaki Kubo and Hidewaki Nakagawa and Tatsuhiko Tsunoda",

note = "Funding Information: This work was supported partially by the National Project on {\textquoteleft}Next-generation Integrated Living Matter Simulation{\textquoteright} and Grant-in-Aid for Young Scientists (B) (Number: 23790389) of Ministry of Education, Culture, Sports, Science and Technology.",

year = "2013",

doi = "10.1038/srep02161",

language = "English",

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T1 - A practical method to detect SNVs and indels from whole genome and exome sequencing data

AU - Shigemizu, Daichi

AU - Fujimoto, Akihiro

AU - Akiyama, Shintaro

AU - Abe, Tetsuo

AU - Nakano, Kaoru

AU - Boroevich, Keith A.

AU - Yamamoto, Yujiro

AU - Furuta, Mayuko

AU - Kubo, Michiaki

AU - Nakagawa, Hidewaki

AU - Tsunoda, Tatsuhiko

N1 - Funding Information: This work was supported partially by the National Project on ‘Next-generation Integrated Living Matter Simulation’ and Grant-in-Aid for Young Scientists (B) (Number: 23790389) of Ministry of Education, Culture, Sports, Science and Technology.

PY - 2013

Y1 - 2013

N2 - 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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A practical method to detect SNVs and indels from whole genome and exome sequencing data

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