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Approaches in Gene Coexpression Analysis in Eukaryotes.

Vasileios L ZogopoulosGeorgia SaxamiApostolos MalatrasKonstantinos PapadopoulosIoanna TsotraVassiliki A IconomidouIoannis Michalopoulos
Published in: Biology (2022)
Gene coexpression analysis constitutes a widely used practice for gene partner identification and gene function prediction, consisting of many intricate procedures. The analysis begins with the collection of primary transcriptomic data and their preprocessing, continues with the calculation of the similarity between genes based on their expression values in the selected sample dataset and results in the construction and visualisation of a gene coexpression network (GCN) and its evaluation using biological term enrichment analysis. As gene coexpression analysis has been studied extensively, we present most parts of the methodology in a clear manner and the reasoning behind the selection of some of the techniques. In this review, we offer a comprehensive and comprehensible account of the steps required for performing a complete gene coexpression analysis in eukaryotic organisms. We comment on the use of RNA-Seq vs. microarrays, as well as the best practices for GCN construction. Furthermore, we recount the most popular webtools and standalone applications performing gene coexpression analysis, with details on their methods, features and outputs.
Keyphrases
  • genome wide
  • copy number
  • healthcare
  • preterm infants
  • dna methylation
  • machine learning
  • multidrug resistant
  • deep learning
  • clinical evaluation