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Pathway Enrichment Analysis of Microarray Data.
Pastrello, Chiara; Niu, Yun; Jurisica, Igor.
Afiliación
  • Pastrello C; Osteoarthritis Research Program, Division of Orthopedic Surgery, Schroeder Arthritis Institute, University Health Network, Toronto, ON, Canada.
  • Niu Y; Data Science Discovery Centre for Chronic Diseases, Krembil Research Institute, Toronto Western Hospital, University Health Network, Toronto, ON, Canada.
  • Jurisica I; Osteoarthritis Research Program, Division of Orthopedic Surgery, Schroeder Arthritis Institute, University Health Network, Toronto, ON, Canada.
Methods Mol Biol ; 2401: 147-159, 2022.
Article en En | MEDLINE | ID: mdl-34902127
Microarray analyses usually result in a list of differential genes that need to be annotated to link them the phenotype being studied, help planning validation experiments and interpretation of the results. Pathway enrichment analyses are frequently used for such purpose, where pathways are human created models of molecular activities and processes. While different types of pathway enrichment are available, we focus this protocol on the most frequent type-overrepresentation analysis. Many databases collect different sets of pathways and curate different sets of genes for the same pathways, so it is important to carefully choose the most suitable pathway source to perform enrichment analysis. To provide a comprehensive pathway analysis, in this protocol we will use pathDIP, which supports comprehensive enrichment analysis by integrating 22 main pathway databases. We will also describe the steps needed to visualize the enriched pathways using GSOAP.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Análisis por Micromatrices Idioma: En Revista: Methods Mol Biol Asunto de la revista: BIOLOGIA MOLECULAR Año: 2022 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Análisis por Micromatrices Idioma: En Revista: Methods Mol Biol Asunto de la revista: BIOLOGIA MOLECULAR Año: 2022 Tipo del documento: Article