An equivalence test between features lists, based on the Sorensen–Dice index and the joint frequencies of GO term enrichment

• Published in: BMC bioinformatics Vol. 23; no. 1; pp. 207 - 21
• Main Authors: Flores, Pablo, Salicrú, Miquel, Sánchez-Pla, Alex, Ocaña, Jordi
• Format: Journal Article
• Language: English
• Published: London BioMed Central 31.05.2022; BioMed Central Ltd; Springer Nature B.V; BMC
• Subjects: Algorithms; Annotations; Bioinformatics; Biomedical and Life Sciences; Bootstrap; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Delta method; Equivalence; Flavors; Gene lists; Genes; Genetic aspects; Genomics; Graft rejection; Hypotheses; Irrelevance of dissimilarity; Life Sciences; Lists; Metabolites; Methods; Microarrays; Normality; Ontology; Simulation; Statistical analysis; Statistical methods; Transplantation; Type I error; Spain; Bootstrap; Gene lists; Type I error; Simulation; Delta method; Irrelevance of dissimilarity
• ISSN: 1471-2105; 1471-2105
• DOI: 10.1186/s12859-022-04739-2

Background In integrative bioinformatic analyses, it is of great interest to stablish the equivalence between gene or (more in general) feature lists, up to a given level and in terms of their annotations in the Gene Ontology. The aim of this article is to present an equivalence test based on the proportion of GO terms which are declared as enriched in both lists simultaneously. Results On the basis of these data, the dissimilarity between gene lists is measured by means of the Sorensen–Dice index. We present two flavours of the same test: One of them based on the asymptotic normality of the test statistic and the other based on the bootstrap method. Conclusions The accuracy of these tests is studied by means of simulation and their possible interest is illustrated by using them over two real datasets: A collection of gene lists related to cancer and a collection of gene lists related to kidney rejection after transplantation.