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webCEMiTool: Co-expression Modular Analysis Made Easy.
Cardozo, Lucas E; Russo, Pedro S T; Gomes-Correia, Bruno; Araujo-Pereira, Mariana; Sepúlveda-Hermosilla, Gonzalo; Maracaja-Coutinho, Vinicius; Nakaya, Helder I.
Afiliación
  • Cardozo LE; Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo, São Paulo, Brazil.
  • Russo PST; Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo, São Paulo, Brazil.
  • Gomes-Correia B; Advanced Center for Chronic Diseases-ACCDiS, Facultad de Ciencias Químicas y Farmacéuticas, Universidad de Chile, Santiago, Chile.
  • Araujo-Pereira M; Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo, São Paulo, Brazil.
  • Sepúlveda-Hermosilla G; Centro de Genómica y Bioinformática, Facultad de Ciencias, Universidad Mayor, Santiago, Chile.
  • Maracaja-Coutinho V; Advanced Center for Chronic Diseases-ACCDiS, Facultad de Ciencias Químicas y Farmacéuticas, Universidad de Chile, Santiago, Chile.
  • Nakaya HI; Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo, São Paulo, Brazil.
Front Genet ; 10: 146, 2019.
Article en En | MEDLINE | ID: mdl-30894872
Co-expression analysis has been widely used to elucidate the functional architecture of genes under different biological processes. Such analysis, however, requires substantial knowledge about programming languages and/or bioinformatics skills. We present webCEMiTool, a unique online tool that performs comprehensive modular analyses in a fully automated manner. The webCEMiTool not only identifies co-expression gene modules but also performs several functional analyses on them. In addition, webCEMiTool integrates transcriptomic data with interactome information (i.e., protein-protein interactions) and identifies potential hubs on each network. The tool generates user-friendly html reports that allow users to search for specific genes in each module, as well as check if a module contains genes overrepresented in specific pathways or altered in a specific sample phenotype. We used webCEMiTool to perform a modular analysis of single-cell RNA-seq data of human cells infected with either Zika virus or dengue virus.
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Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Front Genet Año: 2019 Tipo del documento: Article País de afiliación: Brasil

Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Front Genet Año: 2019 Tipo del documento: Article País de afiliación: Brasil