The differential activity of biological processes in tissues and cell subsets can illuminate disease-related processes and cell type identities

Moran Sharon, Ekaterina Vinogradov, Chanan M. Argov, Or Lazarescu, Yazeed Zoabi, Idan Hekselman, Esti Yeger-Lotem

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Motivation: The distinct functionalities of human tissues and cell types underlie complex phenotype-genotype relationships, yet often remain elusive. Harnessing the multitude of bulk and single-cell human transcriptomes while focusing on processes can help reveal these distinct functionalities. Results: The Tissue-Process Activity (TiPA) method aims to identify processes that are preferentially active or under-expressed in specific contexts, by comparing the expression levels of process genes between contexts. We tested TiPA on 1579 tissue-specific processes and bulk tissue transcriptomes, finding that it performed better than another method. Next, we used TiPA to ask whether the activity of certain processes could underlie the tissue-specific manifestation of 1233 hereditary diseases. We found that 21% of the disease-causing genes indeed participated in such processes, thereby illuminating their genotype-phenotype relationships. Lastly, we applied TiPA to single-cell transcriptomes of 108 human cell types, revealing that process activities often match cell-type identities and can thus aid annotation efforts. Hence, differential activity of processes can highlight the distinct functionality of tissues and cells in a robust and meaningful manner.

Original languageEnglish
Pages (from-to)1584-1592
Number of pages9
JournalBioinformatics
Volume38
Issue number6
Early online date7 Jan 2022
DOIs
StatePublished - 15 Mar 2022

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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