ERDS-pe: A paired hidden Markov model for copy number variant detection from whole-exome sequencing data

Renjie Tan; Jixuan Wang; Xiaoliang Wu; Guoqiang Wan; Rongjie Wang; Rui Ma; Zhijie Han; Wenyang Zhou; Shuilin Jin; Qinghua Jiang; Yadong Wang

doi:10.1109/BIBM.2016.7822508

ERDS-pe: A paired hidden Markov model for copy number variant detection from whole-exome sequencing data

Renjie Tan
, Jixuan Wang
, Xiaoliang Wu
, Guoqiang Wan
, Rongjie Wang
, Rui Ma
, Zhijie Han
, Wenyang Zhou
, Shuilin Jin
, Qinghua Jiang^*
, Yadong Wang

^*Corresponding author for this work

School of Mathematics

School of Computer Science and Technology, Harbin Institute of Technology
Harbin Institute of Technology
School of Life Science and Technology, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

Detecting copy number variants (CNVs) is an essential part in variant calling process. Here, we describe a novel method ERDS-pe to detect CNVs from whole-exome sequencing (WES) data. ERDS-pe first employs principal component analysis to normalize WES data. Then, ERDS-pe incorporates read depth signal and single-nucleotide variation information together as a hybrid signal into a paired hidden Markov model to infer CNVs from WES data. Experimental results on real human WES data show that ERDS-pe demonstrates higher sensitivity and provides comparable or even better specificity than other tools. ERDS-pe is publicly available at: https://github.com/microtan0902/erds-pe.

Original language	English
Title of host publication	Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016
Editors	Kevin Burrage, Qian Zhu, Yunlong Liu, Tianhai Tian, Yadong Wang, Xiaohua Tony Hu, Qinghua Jiang, Jiangning Song, Shinichi Morishita, Kevin Burrage, Guohua Wang
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	141-144
Number of pages	4
ISBN (Electronic)	9781509016105
DOIs	https://doi.org/10.1109/BIBM.2016.7822508
State	Published - 17 Jan 2017
Event	2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016 - Shenzhen, China Duration: 15 Dec 2016 → 18 Dec 2016

Publication series

Name	Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016

Conference

Conference	2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016
Country/Territory	China
City	Shenzhen
Period	15/12/16 → 18/12/16

Keywords

Copy number variation
Hidden Markov model
Principal component analysis
Whole-exome sequencing

Access to Document

10.1109/BIBM.2016.7822508

Cite this

Tan, R., Wang, J., Wu, X., Wan, G., Wang, R., Ma, R., Han, Z., Zhou, W., Jin, S., Jiang, Q., & Wang, Y. (2017). ERDS-pe: A paired hidden Markov model for copy number variant detection from whole-exome sequencing data. In K. Burrage, Q. Zhu, Y. Liu, T. Tian, Y. Wang, X. T. Hu, Q. Jiang, J. Song, S. Morishita, K. Burrage, & G. Wang (Eds.), Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016 (pp. 141-144). Article 7822508 (Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM.2016.7822508

Tan, Renjie ; Wang, Jixuan ; Wu, Xiaoliang et al. / ERDS-pe : A paired hidden Markov model for copy number variant detection from whole-exome sequencing data. Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016. editor / Kevin Burrage ; Qian Zhu ; Yunlong Liu ; Tianhai Tian ; Yadong Wang ; Xiaohua Tony Hu ; Qinghua Jiang ; Jiangning Song ; Shinichi Morishita ; Kevin Burrage ; Guohua Wang. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 141-144 (Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016).

@inproceedings{5c4e8a0961f54227a53c9178c32d3d00,

title = "ERDS-pe: A paired hidden Markov model for copy number variant detection from whole-exome sequencing data",

abstract = "Detecting copy number variants (CNVs) is an essential part in variant calling process. Here, we describe a novel method ERDS-pe to detect CNVs from whole-exome sequencing (WES) data. ERDS-pe first employs principal component analysis to normalize WES data. Then, ERDS-pe incorporates read depth signal and single-nucleotide variation information together as a hybrid signal into a paired hidden Markov model to infer CNVs from WES data. Experimental results on real human WES data show that ERDS-pe demonstrates higher sensitivity and provides comparable or even better specificity than other tools. ERDS-pe is publicly available at: https://github.com/microtan0902/erds-pe.",

keywords = "Copy number variation, Hidden Markov model, Principal component analysis, Whole-exome sequencing",

author = "Renjie Tan and Jixuan Wang and Xiaoliang Wu and Guoqiang Wan and Rongjie Wang and Rui Ma and Zhijie Han and Wenyang Zhou and Shuilin Jin and Qinghua Jiang and Yadong Wang",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016 ; Conference date: 15-12-2016 Through 18-12-2016",

year = "2017",

month = jan,

day = "17",

doi = "10.1109/BIBM.2016.7822508",

language = "英语",

series = "Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "141--144",

editor = "Kevin Burrage and Qian Zhu and Yunlong Liu and Tianhai Tian and Yadong Wang and Hu, \{Xiaohua Tony\} and Qinghua Jiang and Jiangning Song and Shinichi Morishita and Kevin Burrage and Guohua Wang",

booktitle = "Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016",

address = "美国",

}

Tan, R, Wang, J, Wu, X, Wan, G, Wang, R, Ma, R, Han, Z, Zhou, W, Jin, S , Jiang, Q & Wang, Y 2017, ERDS-pe: A paired hidden Markov model for copy number variant detection from whole-exome sequencing data. in K Burrage, Q Zhu, Y Liu, T Tian, Y Wang, XT Hu, Q Jiang, J Song, S Morishita, K Burrage & G Wang (eds), Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016., 7822508, Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016, Institute of Electrical and Electronics Engineers Inc., pp. 141-144, 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016, Shenzhen, China, 15/12/16. https://doi.org/10.1109/BIBM.2016.7822508

ERDS-pe: A paired hidden Markov model for copy number variant detection from whole-exome sequencing data. / Tan, Renjie; Wang, Jixuan; Wu, Xiaoliang et al.
Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016. ed. / Kevin Burrage; Qian Zhu; Yunlong Liu; Tianhai Tian; Yadong Wang; Xiaohua Tony Hu; Qinghua Jiang; Jiangning Song; Shinichi Morishita; Kevin Burrage; Guohua Wang. Institute of Electrical and Electronics Engineers Inc., 2017. p. 141-144 7822508 (Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - ERDS-pe

T2 - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016

AU - Tan, Renjie

AU - Wang, Jixuan

AU - Wu, Xiaoliang

AU - Wan, Guoqiang

AU - Wang, Rongjie

AU - Ma, Rui

AU - Han, Zhijie

AU - Zhou, Wenyang

AU - Jin, Shuilin

AU - Jiang, Qinghua

AU - Wang, Yadong

PY - 2017/1/17

Y1 - 2017/1/17

N2 - Detecting copy number variants (CNVs) is an essential part in variant calling process. Here, we describe a novel method ERDS-pe to detect CNVs from whole-exome sequencing (WES) data. ERDS-pe first employs principal component analysis to normalize WES data. Then, ERDS-pe incorporates read depth signal and single-nucleotide variation information together as a hybrid signal into a paired hidden Markov model to infer CNVs from WES data. Experimental results on real human WES data show that ERDS-pe demonstrates higher sensitivity and provides comparable or even better specificity than other tools. ERDS-pe is publicly available at: https://github.com/microtan0902/erds-pe.

AB - Detecting copy number variants (CNVs) is an essential part in variant calling process. Here, we describe a novel method ERDS-pe to detect CNVs from whole-exome sequencing (WES) data. ERDS-pe first employs principal component analysis to normalize WES data. Then, ERDS-pe incorporates read depth signal and single-nucleotide variation information together as a hybrid signal into a paired hidden Markov model to infer CNVs from WES data. Experimental results on real human WES data show that ERDS-pe demonstrates higher sensitivity and provides comparable or even better specificity than other tools. ERDS-pe is publicly available at: https://github.com/microtan0902/erds-pe.

KW - Copy number variation

KW - Hidden Markov model

KW - Principal component analysis

KW - Whole-exome sequencing

UR - https://www.scopus.com/pages/publications/85013275713

U2 - 10.1109/BIBM.2016.7822508

DO - 10.1109/BIBM.2016.7822508

M3 - 会议稿件

AN - SCOPUS:85013275713

T3 - Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016

SP - 141

EP - 144

BT - Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016

A2 - Burrage, Kevin

A2 - Zhu, Qian

A2 - Liu, Yunlong

A2 - Tian, Tianhai

A2 - Wang, Yadong

A2 - Hu, Xiaohua Tony

A2 - Jiang, Qinghua

A2 - Song, Jiangning

A2 - Morishita, Shinichi

A2 - Burrage, Kevin

A2 - Wang, Guohua

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 15 December 2016 through 18 December 2016

ER -

Tan R, Wang J, Wu X, Wan G, Wang R, Ma R et al. ERDS-pe: A paired hidden Markov model for copy number variant detection from whole-exome sequencing data. In Burrage K, Zhu Q, Liu Y, Tian T, Wang Y, Hu XT, Jiang Q, Song J, Morishita S, Burrage K, Wang G, editors, Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016. Institute of Electrical and Electronics Engineers Inc. 2017. p. 141-144. 7822508. (Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016). doi: 10.1109/BIBM.2016.7822508

ERDS-pe: A paired hidden Markov model for copy number variant detection from whole-exome sequencing data

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