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clusterProfiler:A universal enrichment tool for interpreting omics data
This package supports functional characteristics of both coding and non-coding genomics data for thousands of species with up-to-date gene annotation. It provides a univeral interface for gene functional annotation from a variety of sources and thus can be applied in diverse scenarios. It provides a tidy interface to access, manipulate, and visualize enrichment results to help users achieve efficient data interpretation. Datasets obtained from multiple treatments and time points can be analyzed and compared in a single run, easily revealing functional consensus and differences among distinct conditions.
Maintained by Guangchuang Yu. Last updated 4 months ago.
annotationclusteringgenesetenrichmentgokeggmultiplecomparisonpathwaysreactomevisualizationenrichment-analysisgsea
1.1k stars 17.03 score 11k scripts 48 dependentsbioc
DOSE:Disease Ontology Semantic and Enrichment analysis
This package implements five methods proposed by Resnik, Schlicker, Jiang, Lin and Wang respectively for measuring semantic similarities among DO terms and gene products. Enrichment analyses including hypergeometric model and gene set enrichment analysis are also implemented for discovering disease associations of high-throughput biological data.
Maintained by Guangchuang Yu. Last updated 5 months ago.
annotationvisualizationmultiplecomparisongenesetenrichmentpathwayssoftwaredisease-ontologyenrichment-analysissemantic-similarity
119 stars 14.97 score 2.0k scripts 61 dependentsbioc
ReactomePA:Reactome Pathway Analysis
This package provides functions for pathway analysis based on REACTOME pathway database. It implements enrichment analysis, gene set enrichment analysis and several functions for visualization. This package is not affiliated with the Reactome team.
Maintained by Guangchuang Yu. Last updated 5 months ago.
pathwaysvisualizationannotationmultiplecomparisongenesetenrichmentreactomeenrichment-analysisreactome-pathway-analysisreactomepa
40 stars 12.25 score 1.5k scripts 7 dependentsbioc
meshes:MeSH Enrichment and Semantic analyses
MeSH (Medical Subject Headings) is the NLM controlled vocabulary used to manually index articles for MEDLINE/PubMed. MeSH terms were associated by Entrez Gene ID by three methods, gendoo, gene2pubmed and RBBH. This association is fundamental for enrichment and semantic analyses. meshes supports enrichment analysis (over-representation and gene set enrichment analysis) of gene list or whole expression profile. The semantic comparisons of MeSH terms provide quantitative ways to compute similarities between genes and gene groups. meshes implemented five methods proposed by Resnik, Schlicker, Jiang, Lin and Wang respectively and supports more than 70 species.
Maintained by Guangchuang Yu. Last updated 5 months ago.
annotationclusteringmultiplecomparisonsoftwareenrichment-analysismedical-subject-headingssemantic-similarity
12 stars 7.19 score 43 scripts