knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" )
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:
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.
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")
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)
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.
r BiocStyle::CRANpkg('usethis')
, r BiocStyle::CRANpkg('remotes')
, and r BiocStyle::CRANpkg('rcmdcheck')
customized to use Bioconductor's docker containers and r BiocStyle::Biocpkg('BiocCheck')
.r BiocStyle::CRANpkg('covr')
.r BiocStyle::CRANpkg('pkgdown')
.r BiocStyle::CRANpkg('styler')
.r BiocStyle::CRANpkg('devtools')
and r BiocStyle::CRANpkg('roxygen2')
.For more details, check the dev
directory.
This package was developed using r BiocStyle::Biocpkg('biocthis')
.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.