knitr::opts_chunk$set(
    collapse = TRUE,
    comment = "#>",
    fig.path = "man/figures/README-",
    out.width = "100%"
)

cageminer

GitHub issues Lifecycle: stable R-CMD-check-bioc Codecov test coverage

The goal of cageminer is to integrate SNP data from GWAS results with gene coexpression networks to identify high-confidence candidate genes involved in a particular phenotype. To identify high-confidence candidate genes, cageminer considers 3 criteria:

  1. Physical proximity (or linkage disequilibrium with) trait-related SNPs;
  2. Presence in coexpression modules enriched in guide genes (i.e., "reference" genes that are known to be associated with the phenotype).
  3. Significant altered expression levels in a condition of interest (e.g., stress, disease, etc).

By default, cageminer defines genes as high-confidence candidates if they satisfy all of the 3 criteria above, but users can choose to use only one/some of them.

Installation instructions

Get the latest stable R release from CRAN. Then install cageminer from Bioconductor using the following code:

if (!requireNamespace("BiocManager", quietly = TRUE)) {
    install.packages("BiocManager")
}

BiocManager::install("cageminer")

And the development version from GitHub with:

BiocManager::install("almeidasilvaf/cageminer")

Citation

Below is the citation output from using citation('cageminer') in R. Please run this yourself to check for any updates on how to cite cageminer.

print(citation('cageminer'), bibtex = TRUE)

Code of Conduct

Please note that the cageminer project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

Development tools

For more details, check the dev directory.

This package was developed using r BiocStyle::Biocpkg('biocthis').



almeidasilvaf/cageminer documentation built on Sept. 9, 2023, 5:18 p.m.