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Candidate Gene Miner

Bioconductor version: Release (3.19)

This package aims to integrate GWAS-derived SNPs and coexpression networks to mine candidate genes associated with a particular phenotype. For that, users must define a set of guide genes, which are known genes involved in the studied phenotype. Additionally, the mined candidates can be given a score that favor candidates that are hubs and/or transcription factors. The scores can then be used to rank and select the top n most promising genes for downstream experiments.

Author: Fabrício Almeida-Silva [aut, cre] , Thiago Venancio [aut]

Maintainer: Fabrício Almeida-Silva <fabricio_almeidasilva at>

Citation (from within R, enter citation("cageminer")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

Mining high-confidence candidate genes with cageminer HTML R Script
Reference Manual PDF


biocViews FunctionalGenomics, FunctionalPrediction, GeneExpression, GenomeWideAssociation, Network, NetworkEnrichment, SNP, Software, VariantAnnotation
Version 1.10.0
In Bioconductor since BioC 3.14 (R-4.1) (2.5 years)
License GPL-3
Depends R (>= 4.1)
Imports ggplot2, rlang, ggbio, ggtext, GenomeInfoDb, GenomicRanges, IRanges, reshape2, methods, BioNERO
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Suggests testthat (>= 3.0.0), SummarizedExperiment, knitr, BiocStyle, rmarkdown, covr, sessioninfo
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Follow Installation instructions to use this package in your R session.

Source Package cageminer_1.10.0.tar.gz
Windows Binary (64-bit only)
macOS Binary (x86_64) cageminer_1.10.0.tgz
macOS Binary (arm64) cageminer_1.10.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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