EviNet: a Web Platform for Network Enrichment Analysis with Flexible Definition of Gene Sets

Overview

Journal Nucleic Acids Res

Publisher Oxford University Press

Specialty Biochemistry

Date 2018 Jun 13

PMID 29893885

Citations 14

Authors

Ashwini Jeggari

Zhanna Alekseenko

Iurii Petrov

Jose M Dias

Johan Ericson

Andrey Alexeyenko

Affiliations

Soon will be listed here.

Abstract

The new web resource EviNet provides an easily run interface to network enrichment analysis for exploration of novel, experimentally defined gene sets. The major advantages of this analysis are (i) applicability to any genes found in the global network rather than only to those with pathway/ontology term annotations, (ii) ability to connect genes via different molecular mechanisms rather than within one high-throughput platform, and (iii) statistical power sufficient to detect enrichment of very small sets, down to individual genes. The users' gene sets are either defined prior to upload or derived interactively from an uploaded file by differential expression criteria. The pathways and networks used in the analysis can be chosen from the collection menu. The calculation is typically done within seconds or minutes and the stable URL is provided immediately. The results are presented in both visual (network graphs) and tabular formats using jQuery libraries. Uploaded data and analysis results are kept in separated project directories not accessible by other users. EviNet is available at https://www.evinet.org/.

Citing Articles

Benchmarking enrichment analysis methods with the disease pathway network.

Buzzao D, Castresana-Aguirre M, Guala D, Sonnhammer E Brief Bioinform. 2024; 25(2).

PMID: 38436561 PMC: 10939300. DOI: 10.1093/bib/bbae069.

Unraveling the causal genes and transcriptomic determinants of human telomere length.

Chang Y, Zhou Y, Zhou J, Li W, Cao J, Jing Y Nat Commun. 2023; 14(1):8517.

PMID: 38129441 PMC: 10739845. DOI: 10.1038/s41467-023-44355-z.

Gene set correlation enrichment analysis for interpreting and annotating gene expression profiles.

Chang L, Lee M, Wu Y, Lee W, Ma C, Chang J Nucleic Acids Res. 2023; 52(3):e17.

PMID: 38096046 PMC: 10853793. DOI: 10.1093/nar/gkad1187.

IndepthPathway: an integrated tool for in-depth pathway enrichment analysis based on single-cell sequencing data.

Lee S, Deng L, Wang Y, Wang K, Sartor M, Wang X Bioinformatics. 2023; 39(6).

PMID: 37243667 PMC: 10275909. DOI: 10.1093/bioinformatics/btad325.

PathBIX-a web server for network-based pathway annotation with adaptive null models.

Castresana-Aguirre M, Persson E, Sonnhammer E Bioinform Adv. 2023; 1(1):vbab010.

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