COCOA
Coordinate Covariation Analysis
Bioconductor version: 3.24 · Package version: 2.27.0
COCOA is a method for understanding epigenetic variation among samples. COCOA can be used with epigenetic data that includes genomic coordinates and an epigenetic signal, such as DNA methylation and chromatin accessibility data. To describe the method on a high level, COCOA quantifies inter-sample variation with either a supervised or unsupervised technique then uses a database of "region sets" to annotate the variation among samples. A region set is a set of genomic regions that share a biological annotation, for instance transcription factor (TF) binding regions, histone modification regions, or open chromatin regions. COCOA can identify region sets that are associated with epigenetic variation between samples and increase understanding of variation in your data.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("COCOA") Details
| Maintainer | John Lawson <jtl2hk@virginia.edu> |
| Author | John Lawson [aut, cre], Nathan Sheffield [aut] (http://www.databio.org), Jason Smith [ctb] |
| License | GPL-3 |
| URL | http://code.databio.org/COCOA/ |
| Bug Reports | https://github.com/databio/COCOA |
| Downloads rank | 599 |
| Source branch | devel |
| biocViews | ATACSeq, ChIPSeq, DNAMethylation, DNaseSeq, Epigenetics, FunctionalGenomics, GeneRegulation, GenomeAnnotation, GenomicVariation, ImmunoOncology, MethylSeq, MethylationArray, PrincipalComponent, Sequencing, Software, SystemsBiology |
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | COCOA_2.27.0.tar.gz |
| Windows binary (x86_64) | COCOA_2.27.0.zip |
| macOS binary (arm64) | COCOA_2.27.0.tgz |
| macOS binary (x86_64) | COCOA_2.27.0.tgz |
Dependencies
Depends: R (>= 3.5), GenomicRanges
Imports: BiocGenerics, S4Vectors, IRanges, data.table, ggplot2, Biobase, stats, methods, ComplexHeatmap, MIRA, tidyr, grid, grDevices, simpleCache, fitdistrplus
Suggests: knitr, parallel, testthat, BiocStyle, rmarkdown, AnnotationHub, LOLA