An automated quality control pipeline for eQTL analysis with RNA-seq data

Tao Wang; Junpeng Ruan; Quanwei Yin; Xianjun Dong; Yadong Wang

doi:10.1109/BIBM47256.2019.8983006

An automated quality control pipeline for eQTL analysis with RNA-seq data

Tao Wang
, Junpeng Ruan
, Quanwei Yin
, Xianjun Dong
, Yadong Wang

School of Computer Science and Technology, Harbin Institute of Technology
Northwestern Polytechnical University Xian
Brigham and Women’s Hospital

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

6 Scopus citations

Abstract

Expression quantitative trait loci (eQTL) analysis is of critical importance to understand the mechanism underlying trait associated variants. Evaluating and controlling the data quality of transcripts and genotypes, which are basis of eQTL analysis, remains challenging for researchers with limited computational backgrounds. There is a strong need for a user-friendly and comprehensive tool to pre-process those data sets automatically. Here we propose such a solution, eQTLQC, an automated quality control pipeline for preprocessing both RNA-seq and genotype data. The eQTLQC pipeline provides multiple informative quality control measurements and data normalization approaches. And it provides a easy-to-use configuration file for users to flexibly set up the parameters and control the pipeline. We demonstrate its utility by performing RNA-seq and genotype preprocessing on real data sets. eQTLQC is open source and freely available at https://github.com/ruanjunpeng/eQTLQC.

Original language	English
Title of host publication	Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019
Editors	Illhoi Yoo, Jinbo Bi, Xiaohua Tony Hu
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1780-1786
Number of pages	7
ISBN (Electronic)	9781728118673
DOIs	https://doi.org/10.1109/BIBM47256.2019.8983006
State	Published - Nov 2019
Externally published	Yes
Event	2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019 - San Diego, United States Duration: 18 Nov 2019 → 21 Nov 2019

Publication series

Name	Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019

Conference

Conference	2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019
Country/Territory	United States
City	San Diego
Period	18/11/19 → 21/11/19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

RNA-seq
eQTL
genotype
pipeline
quality control

Access to Document

10.1109/BIBM47256.2019.8983006

Cite this

Wang, T., Ruan, J., Yin, Q., Dong, X., & Wang, Y. (2019). An automated quality control pipeline for eQTL analysis with RNA-seq data. In I. Yoo, J. Bi, & X. T. Hu (Eds.), Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019 (pp. 1780-1786). Article 8983006 (Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM47256.2019.8983006

Wang, Tao ; Ruan, Junpeng ; Yin, Quanwei et al. / An automated quality control pipeline for eQTL analysis with RNA-seq data. Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019. editor / Illhoi Yoo ; Jinbo Bi ; Xiaohua Tony Hu. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 1780-1786 (Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019).

@inproceedings{7bac8036ea1e4b2eaec1cfa1c0948e09,

title = "An automated quality control pipeline for eQTL analysis with RNA-seq data",

abstract = "Expression quantitative trait loci (eQTL) analysis is of critical importance to understand the mechanism underlying trait associated variants. Evaluating and controlling the data quality of transcripts and genotypes, which are basis of eQTL analysis, remains challenging for researchers with limited computational backgrounds. There is a strong need for a user-friendly and comprehensive tool to pre-process those data sets automatically. Here we propose such a solution, eQTLQC, an automated quality control pipeline for preprocessing both RNA-seq and genotype data. The eQTLQC pipeline provides multiple informative quality control measurements and data normalization approaches. And it provides a easy-to-use configuration file for users to flexibly set up the parameters and control the pipeline. We demonstrate its utility by performing RNA-seq and genotype preprocessing on real data sets. eQTLQC is open source and freely available at https://github.com/ruanjunpeng/eQTLQC.",

keywords = "RNA-seq, eQTL, genotype, pipeline, quality control",

author = "Tao Wang and Junpeng Ruan and Quanwei Yin and Xianjun Dong and Yadong Wang",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019 ; Conference date: 18-11-2019 Through 21-11-2019",

year = "2019",

month = nov,

doi = "10.1109/BIBM47256.2019.8983006",

language = "英语",

series = "Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019",

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

pages = "1780--1786",

editor = "Illhoi Yoo and Jinbo Bi and Hu, \{Xiaohua Tony\}",

booktitle = "Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019",

address = "美国",

}

Wang, T, Ruan, J, Yin, Q, Dong, X & Wang, Y 2019, An automated quality control pipeline for eQTL analysis with RNA-seq data. in I Yoo, J Bi & XT Hu (eds), Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019., 8983006, Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019, Institute of Electrical and Electronics Engineers Inc., pp. 1780-1786, 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019, San Diego, United States, 18/11/19. https://doi.org/10.1109/BIBM47256.2019.8983006

An automated quality control pipeline for eQTL analysis with RNA-seq data. / Wang, Tao; Ruan, Junpeng; Yin, Quanwei et al.
Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019. ed. / Illhoi Yoo; Jinbo Bi; Xiaohua Tony Hu. Institute of Electrical and Electronics Engineers Inc., 2019. p. 1780-1786 8983006 (Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019).

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

TY - GEN

T1 - An automated quality control pipeline for eQTL analysis with RNA-seq data

AU - Wang, Tao

AU - Ruan, Junpeng

AU - Yin, Quanwei

AU - Dong, Xianjun

AU - Wang, Yadong

PY - 2019/11

Y1 - 2019/11

N2 - Expression quantitative trait loci (eQTL) analysis is of critical importance to understand the mechanism underlying trait associated variants. Evaluating and controlling the data quality of transcripts and genotypes, which are basis of eQTL analysis, remains challenging for researchers with limited computational backgrounds. There is a strong need for a user-friendly and comprehensive tool to pre-process those data sets automatically. Here we propose such a solution, eQTLQC, an automated quality control pipeline for preprocessing both RNA-seq and genotype data. The eQTLQC pipeline provides multiple informative quality control measurements and data normalization approaches. And it provides a easy-to-use configuration file for users to flexibly set up the parameters and control the pipeline. We demonstrate its utility by performing RNA-seq and genotype preprocessing on real data sets. eQTLQC is open source and freely available at https://github.com/ruanjunpeng/eQTLQC.

AB - Expression quantitative trait loci (eQTL) analysis is of critical importance to understand the mechanism underlying trait associated variants. Evaluating and controlling the data quality of transcripts and genotypes, which are basis of eQTL analysis, remains challenging for researchers with limited computational backgrounds. There is a strong need for a user-friendly and comprehensive tool to pre-process those data sets automatically. Here we propose such a solution, eQTLQC, an automated quality control pipeline for preprocessing both RNA-seq and genotype data. The eQTLQC pipeline provides multiple informative quality control measurements and data normalization approaches. And it provides a easy-to-use configuration file for users to flexibly set up the parameters and control the pipeline. We demonstrate its utility by performing RNA-seq and genotype preprocessing on real data sets. eQTLQC is open source and freely available at https://github.com/ruanjunpeng/eQTLQC.

KW - RNA-seq

KW - eQTL

KW - genotype

KW - pipeline

KW - quality control

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DO - 10.1109/BIBM47256.2019.8983006

M3 - 会议稿件

AN - SCOPUS:85084340764

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SP - 1780

EP - 1786

BT - Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019

A2 - Yoo, Illhoi

A2 - Bi, Jinbo

A2 - Hu, Xiaohua Tony

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019

Y2 - 18 November 2019 through 21 November 2019

ER -

Wang T, Ruan J, Yin Q, Dong X, Wang Y. An automated quality control pipeline for eQTL analysis with RNA-seq data. In Yoo I, Bi J, Hu XT, editors, Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 1780-1786. 8983006. (Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019). doi: 10.1109/BIBM47256.2019.8983006

An automated quality control pipeline for eQTL analysis with RNA-seq data

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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