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

Guangsheng Pei1, Yulin Dai1, Zhongming Zhao1,2,3

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This study introduces deTS, an R package for tissue-specific enrichment analysis. deTS effectively identifies relevant tissues for traits and samples, enhancing the power of biomedical studies.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Systems Biology

Background:

  • Biological traits and diseases exhibit dynamic, tissue-specific regulation.
  • Using heterogeneous tissues in studies can dilute the identification of disease-associated variants and gene expression patterns.

Purpose of the Study:

  • To develop and present deTS, an R package designed for tissue-specific enrichment analysis.
  • To provide statistical methods for identifying tissue-specific genes and performing enrichment tests on various data types.

Main Methods:

  • Development of the deTS R package.
  • Implementation of statistical methods for tissue-specific gene detection.
  • Application of deTS to multi-trait genome-wide association studies (GWAS) and cancer expression data.

Main Results:

  • deTS successfully performs tissue-specific enrichment analysis using built-in reference panels.
  • The package effectively identifies the most relevant tissues for queried traits or samples.
  • Applications demonstrated improved insights for multi-trait GWAS and cancer expression analyses.

Conclusions:

  • deTS enhances the power of biomedical studies by enabling tissue-specific analysis.
  • The package offers valuable insights for future research by pinpointing relevant tissues.
  • deTS is available as an R package on CRAN and GitHub.