deTS: tissue-specific enrichment analysis to decode tissue specificity.

Pei, Guangsheng; Dai, Yulin; Zhao, Zhongming; Jia, Peilin · Bioinformatics · 2019

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Abstract

Diseases and traits are under dynamic tissue-specific regulation. However, heterogeneous tissues are often collected in biomedical studies, which reduce the power in the identification of disease-associated variants and gene expression profiles. We present deTS, an R package, to conduct tissue-specific enrichment analysis with two built-in reference panels. Statistical methods are developed and implemented for detecting tissue-specific genes and for enrichment test of different forms of query data. Our applications using multi-trait genome-wide association studies data and cancer expression data showed that deTS could effectively identify the most relevant tissues for each query trait or sample, providing insights for future studies. https://github.com/bsml320/deTS and CRAN https://cran.r-project.org/web/packages/deTS/. Supplementary data are available at Bioinformatics online.

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