GSAn: an alternative to enrichment analysis for annotating gene sets.

ABSTRACT: The revolution in new sequencing technologies is greatly leading to new understandings of the relations between genotype and phenotype. To interpret and analyze data that are grouped according to a phenotype of interest, methods based on statistical enrichment became a standard in biology. However, these methods synthesize the biological information by a priori selecting the over-represented terms and may suffer from focusing on the most studied genes that represent a limited coverage of annotated genes within a gene set. Semantic similarity measures have shown great results within the pairwise gene comparison by making advantage of the underlying structure of the Gene Ontology. We developed GSAn, a novel gene set annotation method that uses semantic similarity measures to synthesiz

SUBMITTER: Ayllon-Benitez A 

PROVIDER: S-EPMC7671311 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature