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MOTIVATION: 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. RESULTS: 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. AVAILABILITY AND IMPLEMENTATION: https://github.com/bsml320/deTS and CRAN https://cran.r-project.org/web/packages/deTS/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Pei et al. (2019) studied this question.
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