Gene Set Enrichment Meta-Analysis
Overview
Performing the different steps of gene set enrichment meta-analysis. It provides different functions that allow the application of meta-analysis based on the combination of effect sizes from different pathways in different studies to obtain significant pathways that are common to all of them.
Install
Health
ERRORpackage dependenciesr-patched-linux-x86_64
Package required but not available: ‘GSVA’ See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’ manual.
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- OK13 OK2026-09-11
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Documentation
- Help pages
- 6
- Examples that run
- 100%5 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 92%
- Return-value docs
- 100%
- Help pages citing references
- 83% with Rdpack citation macros
Downloads
Dependencies
Installing GSEMA adds 31 packages (9 with compiled code, 19 MB of source tarballs). Heaviest: metafor 4.8 MB, mathjaxr 3.0 MB, Rcpp 1.8 MB. 5 more not on CRAN are not measured.
Code & Tests
Datasets
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- unarchivedReturned to CRAN2025-10-16
- 0.99.4Latest
- archivedRemoved from CRAN2025-10-11multiple policy violations Spammed personal address in HTML Requires package unavailable in mainstream repository
- RR 4.5.0 released · 2025-04-11
- 0.99.32024-10-14
- RR 4.4.0 released · 2024-04-24
Package metadata
- First published
- 2024-10-14
- Total releases
- 2 / 2 yrs
- License
- GPL-2 OSI
- Minimum R
- ≥ 4.4
- Bundled data
- 3.2 MB / 2 files
- Download size
- 3.6 MB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("GSEMA")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-23, which the citation names so these numbers can be found later. More on citing and the projects behind them.