An effective analytic method for detecting tissue-specific genes in RNA-seq experiments

Guoqing Zhao; Qiao Li; I. Ming Wang; Xiaoqiao Liu; Xiangzhong Fang; Xiaohua Douglas Zhang

doi:10.2217/pgs.15.118

An effective analytic method for detecting tissue-specific genes in RNA-seq experiments

Guoqing Zhao, Qiao Li, I. Ming Wang, Xiaoqiao Liu, Xiangzhong Fang, Xiaohua Douglas Zhang

Biostatistics

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

2 Scopus citations

Abstract

Aim: To develop an analytic method for identifying tissue-specific (TS) genes from RNA-seq data. Materials & methods: Based on a negative binomial distribution, we develop a statistical method containing consecutive procedures incorporating data variability from replicates in each tissue. Results: Simulations show that our approach can effectively identify at least 94% of the truly TS genes if the sample size is 3 and at least 84% of the TS genes detected by our method are truly TS genes. We illustrated the utility of our method in an in-house RNA-seq project and produced sensible results. Conclusion: Our approach not only directly works on discrete data but also naturally incorporates data variability. It works effectively for detecting TS genes.

Original language	English
Pages (from-to)	1769-1779
Number of pages	11
Journal	Pharmacogenomics
Volume	16
Issue number	16
DOIs	https://doi.org/10.2217/pgs.15.118
State	Published - Nov 2015

Bibliographical note

Publisher Copyright:
© 2015 Future Medicine Ltd.

Keywords

RNA-Seq
consecutive procedures
generalization of Tukey's test
next-generation sequencing
tissue-specific gene

ASJC Scopus subject areas

Molecular Medicine
Genetics
Pharmacology

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10.2217/pgs.15.118

Cite this

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abstract = "Aim: To develop an analytic method for identifying tissue-specific (TS) genes from RNA-seq data. Materials & methods: Based on a negative binomial distribution, we develop a statistical method containing consecutive procedures incorporating data variability from replicates in each tissue. Results: Simulations show that our approach can effectively identify at least 94% of the truly TS genes if the sample size is 3 and at least 84% of the TS genes detected by our method are truly TS genes. We illustrated the utility of our method in an in-house RNA-seq project and produced sensible results. Conclusion: Our approach not only directly works on discrete data but also naturally incorporates data variability. It works effectively for detecting TS genes.",

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AU - Wang, I. Ming

AU - Liu, Xiaoqiao

AU - Fang, Xiangzhong

AU - Zhang, Xiaohua Douglas

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KW - generalization of Tukey's test

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An effective analytic method for detecting tissue-specific genes in RNA-seq experiments

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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