AUTHOR=Chicco Davide , Jurman Giuseppe 

TITLE=A brief survey of tools for genomic regions enrichment analysis

JOURNAL=Frontiers in Bioinformatics

VOLUME=Volume 2 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/bioinformatics/articles/10.3389/fbinf.2022.968327

DOI=10.3389/fbinf.2022.968327

ISSN=2673-7647

ABSTRACT=Functional enrichment analysis or pathway enrichment analysis (PEA) is a bioinformatics technique which identifies the most over-represented biological pathways in a list of genes, compared to the ones that would be associated with them by chance. These biological functions are found on bioinformatics annotated databases such as the Gene Ontology or KEGG, for example, and the identification of more abundant pathways is done through statistical techniques, such as Fisher’s exact test or others. All PEA tools require a list of genes as input. Few tools, however, read lists of genomic regions as input rather than lists of genes, and perform an association between these chromosome regions and their corresponding genes first. These tools perform a procedure called genomic regions enrichment analysis, and can be useful to users wanting to detect the biological pathways related to a set of chromosome regions. In this brief survey, we analyze six tools for genomic regions enrichment analysis (BEHST, g:Profiler g:GOSt, GREAT, LOLA, Poly-Enrich, and ReactomePA), outlining and comparing their main features. Our comparison results indicate that the inclusion of data of regulatory elements, such as ChIP-seq, is common among these tools and therefore is believed to improve the enrichment analysis results.