Pathway enrichment analysis and visualization of omics data using g:Profiler, GSEA, Cytoscape and EnrichmentMap.

Computational Biology / methods Databases, Genetic Datasets as Topic Gene Expression Profiling Gene Expression Regulation, Neoplastic Gene Regulatory Networks Genome, Human Humans Immunity, Innate Neoplasm Proteins / genetics Neoplasms / genetics Protein Interaction Mapping / methods Software

Journal

Nature protocols
ISSN: 1750-2799
Titre abrégé: Nat Protoc
Pays: England
ID NLM: 101284307

Informations de publication

Date de publication:
02 2019
Historique:
pubmed: 22 1 2019
medline: 18 4 2019
entrez: 22 1 2019
Statut: ppublish

Résumé

Pathway enrichment analysis helps researchers gain mechanistic insight into gene lists generated from genome-scale (omics) experiments. This method identifies biological pathways that are enriched in a gene list more than would be expected by chance. We explain the procedures of pathway enrichment analysis and present a practical step-by-step guide to help interpret gene lists resulting from RNA-seq and genome-sequencing experiments. The protocol comprises three major steps: definition of a gene list from omics data, determination of statistically enriched pathways, and visualization and interpretation of the results. We describe how to use this protocol with published examples of differentially expressed genes and mutated cancer genes; however, the principles can be applied to diverse types of omics data. The protocol describes innovative visualization techniques, provides comprehensive background and troubleshooting guidelines, and uses freely available and frequently updated software, including g:Profiler, Gene Set Enrichment Analysis (GSEA), Cytoscape and EnrichmentMap. The complete protocol can be performed in ~4.5 h and is designed for use by biologists with no prior bioinformatics training.

Identifiants

DOI: 10.1038/s41596-018-0103-9 PMID: 30664679 PMC: PMC6607905
pubmed: 30664679
doi: 10.1038/s41596-018-0103-9
pii: 10.1038/s41596-018-0103-9
pmc: PMC6607905
mid: NIHMS1032148
doi:

Substances chimiques

Neoplasm Proteins 0

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

482-517

Subventions

Organisme : NCI NIH HHS
ID : R33 CA183654
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA130826
Pays : United States
Organisme : NIGMS NIH HHS
ID : P41 GM103504
Pays : United States
Organisme : NHGRI NIH HHS
ID : R01 HG009979
Pays : United States
Organisme : NIAID NIH HHS
ID : R01 AI073724
Pays : United States

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Auteurs

Jüri Reimand (J)

Computational Biology Program, Ontario Institute for Cancer Research, Toronto, ON, Canada.
Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.

Ruth Isserlin (R)

The Donnelly Centre, University of Toronto, Toronto, ON, Canada.
ORCID: 0000-0002-6805-2080

Veronique Voisin (V)

The Donnelly Centre, University of Toronto, Toronto, ON, Canada.

Mike Kucera (M)

The Donnelly Centre, University of Toronto, Toronto, ON, Canada.

Christian Tannus-Lopes (C)

The Donnelly Centre, University of Toronto, Toronto, ON, Canada.

Asha Rostamianfar (A)

The Donnelly Centre, University of Toronto, Toronto, ON, Canada.

Lina Wadi (L)

Computational Biology Program, Ontario Institute for Cancer Research, Toronto, ON, Canada.

Mona Meyer (M)

Computational Biology Program, Ontario Institute for Cancer Research, Toronto, ON, Canada.

Jeff Wong (J)

The Donnelly Centre, University of Toronto, Toronto, ON, Canada.

Changjiang Xu (C)

The Donnelly Centre, University of Toronto, Toronto, ON, Canada.

Daniele Merico (D)

Deep Genomics Inc., Toronto, ON, Canada.
The Centre for Applied Genomics (TCAG), The Hospital for Sick Children, Toronto, ON, Canada.
ORCID: 0000-0002-3728-4401

Gary D Bader (GD)

The Donnelly Centre, University of Toronto, Toronto, ON, Canada. gary.bader@utoronto.ca.
Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada. gary.bader@utoronto.ca.
Department of Computer Science, University of Toronto, Toronto, ON, Canada. gary.bader@utoronto.ca.
ORCID: 0000-0003-0185-8861

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Classifications MeSH

questionsmedicales.fr › Sciences de l'information › Informatique › Biologie informatique › Pathway enrichment analysis and visualization...
questionsmedicales.fr › Sciences de l'information › Mémorisation et recherche des informations › Bases de données comme sujet › Bases de données factuelles › Bases de données génétiques › Pathway enrichment analysis and visualization...
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questionsmedicales.fr › Techniques d'investigation › Techniques génétiques › Analyse de profil d'expression de gènes › Pathway enrichment analysis and visualization...
questionsmedicales.fr › Phénomènes génétiques › Régulation de l'expression des gènes › Régulation de l'expression des gènes tumoraux › Pathway enrichment analysis and visualization...
questionsmedicales.fr › Phénomènes génétiques › Structures génétiques › Séquences d'acides nucléiques régulatrices › Réseaux de régulation génique › Pathway enrichment analysis and visualization...
questionsmedicales.fr › Phénomènes génétiques › Structures génétiques › Génome › Génome humain › Pathway enrichment analysis and visualization...
questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › Pathway enrichment analysis and visualization...
questionsmedicales.fr › Phénomènes du système immunitaire › Immunité › Immunité innée › Pathway enrichment analysis and visualization...
questionsmedicales.fr › Acides aminés, peptides et protéines › Protéines › Protéines tumorales › Pathway enrichment analysis and visualization...
questionsmedicales.fr › Tumeurs › Pathway enrichment analysis and visualization...
questionsmedicales.fr › Techniques d'investigation › Techniques de sonde moléculaire › Cartographie d'interactions entre protéines › Pathway enrichment analysis and visualization...
questionsmedicales.fr › Sciences de l'information › Méthodologies informatiques › Logiciel › Pathway enrichment analysis and visualization...