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https://github.com/databio/cocoa

Annotating epigenetic variation among samples with region sets in R

https://github.com/databio/cocoa

Science Score: 26.0%

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Keywords

dna-methylation pca
Last synced: 5 months ago · JSON representation

Repository

Annotating epigenetic variation among samples with region sets in R

Basic Info
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  • Stars: 10
  • Watchers: 10
  • Forks: 0
  • Open Issues: 3
  • Releases: 0
Topics
dna-methylation pca
Created almost 8 years ago · Last pushed about 1 year ago
Metadata Files
Readme Changelog License

README.md

COCOA: Coordinate Covariation Analysis

Build Status 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.

Installing COCOA

To install from Bioconductor (recommended):

```{r, eval=FALSE, message=FALSE, warning=FALSE} if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager")

BiocManager::install("COCOA") ```

COCOA may also be installed from Github:

{r, eval=FALSE, message=FALSE, warning=FALSE} devtools::install_github("databio/COCOA")

or locally after downloading/cloning the source code:

{r, eval=FALSE, message=FALSE, warning=FALSE} install.packages("path/to/COCOA/directory", repos=NULL, type="source")

Learning How to Use COCOA

A vignette is included with the package that shows an overview of COCOA and walks you through multiple analysis scenarios with code.

Owner

  • Name: Databio
  • Login: databio
  • Kind: organization
  • Location: University of Virginia

Solving problems in computational biology

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Top Authors
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  • kinganimz (13)
  • nsheff (13)
  • j-lawson (9)
  • AlexWixom (1)
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  • j-lawson (15)
  • kinganimz (5)
  • nsheff (1)
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Dependencies

DESCRIPTION cran
  • GenomicRanges * depends
  • R >= 3.5 depends
  • Biobase * imports
  • BiocGenerics * imports
  • ComplexHeatmap * imports
  • IRanges * imports
  • MIRA * imports
  • S4Vectors * imports
  • data.table * imports
  • fitdistrplus * imports
  • ggplot2 * imports
  • grDevices * imports
  • grid * imports
  • methods * imports
  • simpleCache * imports
  • stats * imports
  • tidyr * imports
  • AnnotationHub * suggests
  • BiocStyle * suggests
  • LOLA * suggests
  • knitr * suggests
  • parallel * suggests
  • rmarkdown * suggests
  • testthat * suggests