Cells (Jan 2023)

HGCA2.0: An RNA-Seq Based Webtool for Gene Coexpression Analysis in <i>Homo sapiens</i>

  • Vasileios L. Zogopoulos,
  • Apostolos Malatras,
  • Konstantinos Kyriakidis,
  • Chrysanthi Charalampous,
  • Evanthia A. Makrygianni,
  • Stéphanie Duguez,
  • Marianna A. Koutsi,
  • Marialena Pouliou,
  • Christos Vasileiou,
  • William J. Duddy,
  • Marios Agelopoulos,
  • George P. Chrousos,
  • Vassiliki A. Iconomidou,
  • Ioannis Michalopoulos

DOI
https://doi.org/10.3390/cells12030388
Journal volume & issue
Vol. 12, no. 3
p. 388

Abstract

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Genes with similar expression patterns in a set of diverse samples may be considered coexpressed. Human Gene Coexpression Analysis 2.0 (HGCA2.0) is a webtool which studies the global coexpression landscape of human genes. The website is based on the hierarchical clustering of 55,431 Homo sapiens genes based on a large-scale coexpression analysis of 3500 GTEx bulk RNA-Seq samples of healthy individuals, which were selected as the best representative samples of each tissue type. HGCA2.0 presents subclades of coexpressed genes to a gene of interest, and performs various built-in gene term enrichment analyses on the coexpressed genes, including gene ontologies, biological pathways, protein families, and diseases, while also being unique in revealing enriched transcription factors driving coexpression. HGCA2.0 has been successful in identifying not only genes with ubiquitous expression patterns, but also tissue-specific genes. Benchmarking showed that HGCA2.0 belongs to the top performing coexpression webtools, as shown by STRING analysis. HGCA2.0 creates working hypotheses for the discovery of gene partners or common biological processes that can be experimentally validated. It offers a simple and intuitive website design and user interface, as well as an API endpoint.

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