PhenoExam: gene set analyses through integration of different phenotype databases

Author:

Cisterna Alejandro,González-Vidal Aurora,Ruiz Daniel,Ortiz Jordi,Gómez-Pascual Alicia,Chen Zhongbo,Nalls Mike,Faghri Faraz,Hardy John,Díez Irene,Maietta Paolo,Álvarez Sara,Ryten Mina,Botía Juan A.ORCID

Abstract

Abstract Background Gene set enrichment analysis (detecting phenotypic terms that emerge as significant in a set of genes) plays an important role in bioinformatics focused on diseases of genetic basis. To facilitate phenotype-oriented gene set analysis, we developed PhenoExam, a freely available R package for tool developers and a web interface for users, which performs: (1) phenotype and disease enrichment analysis on a gene set; (2) measures statistically significant phenotype similarities between gene sets and (3) detects significant differential phenotypes or disease terms across different databases. Results PhenoExam generates sensitive and accurate phenotype enrichment analyses. It is also effective in segregating gene sets or Mendelian diseases with very similar phenotypes. We tested the tool with two similar diseases (Parkinson and dystonia), to show phenotype-level similarities but also potentially interesting differences. Moreover, we used PhenoExam to validate computationally predicted new genes potentially associated with epilepsy. Conclusions We developed PhenoExam, a freely available R package and Web application, which performs phenotype enrichment and disease enrichment analysis on gene set G, measures statistically significant phenotype similarities between pairs of gene sets G and G′ and detects statistically significant exclusive phenotypes or disease terms, across different databases. We proved with simulations and real cases that it is useful to distinguish between gene sets or diseases with very similar phenotypes. Github R package URL is https://github.com/alexcis95/PhenoExam. Shiny App URL is https://alejandrocisterna.shinyapps.io/phenoexamweb/.

Funder

Fundación Séneca

Medical Research Council

Wellcome Trust

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Structural Biology

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