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PhenoExam: gene set analyses through integration of different phenotype databases.
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.
Afiliación
  • Cisterna A; Departamento de Ingeniería de la Información y las Comunicaciones, Universidad de Murcia, Murcia, Spain.
  • González-Vidal A; Departamento de Ingeniería de la Información y las Comunicaciones, Universidad de Murcia, Murcia, Spain.
  • Ruiz D; Departamento de Ingeniería de la Información y las Comunicaciones, Universidad de Murcia, Murcia, Spain.
  • Ortiz J; Departamento de Ingeniería de la Información y las Comunicaciones, Universidad de Murcia, Murcia, Spain.
  • Gómez-Pascual A; Departamento de Ingeniería de la Información y las Comunicaciones, Universidad de Murcia, Murcia, Spain.
  • Chen Z; Department of Neurodegenerative Disease, UCL, Institute of Neurology, London, UK.
  • Nalls M; Data Tecnica International LLC, Glen Echo, MD, USA.
  • Faghri F; Laboratory of Neurogenetics, NIA/NIH, Bethesda, MD, USA.
  • Hardy J; Center for Alzheimer's and Related Dememtias, NIH, Bethesda, MD, USA.
  • Díez I; Data Tecnica International LLC, Glen Echo, MD, USA.
  • Maietta P; Laboratory of Neurogenetics, NIA/NIH, Bethesda, MD, USA.
  • Álvarez S; Center for Alzheimer's and Related Dememtias, NIH, Bethesda, MD, USA.
  • Ryten M; Department of Neurodegenerative Disease, UCL, Institute of Neurology, London, UK.
  • Botía JA; Reta Lila Weston Institute, UCL Queen Square Institute of Neurology, London, UK.
BMC Bioinformatics ; 23(1): 567, 2022 Dec 31.
Article en En | MEDLINE | ID: mdl-36587217
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/ .
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Biología Computacional Idioma: En Revista: BMC Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: España

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Biología Computacional Idioma: En Revista: BMC Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: España