Package: COCOA 2.21.0

John Lawson

COCOA: Coordinate Covariation Analysis

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.

Authors:John Lawson [aut, cre], Nathan Sheffield [aut], Jason Smith [ctb]

COCOA_2.21.0.tar.gz
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COCOA.pdf |COCOA.html✨
COCOA/json (API)
NEWS

# Install 'COCOA' in R:
install.packages('COCOA', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/databio/cocoa/issues

Datasets:
  • atf3_chr1 - Atf3 binding regions.
  • brcaATACCoord1 - A GRanges object with coordinates for select BRCA ATAC-seq peak regions from chr1.
  • brcaATACData1 - A matrix with ATAC-seq counts in select peak regions from chromosome 1 for 37 patients.
  • brcaMCoord1 - A GRanges object with genomic coordinates for cytosines from chr1 for the package's built-in DNA methylation data
  • brcaMetadata - A data.frame with patient metadata for breast cancer patients.
  • brcaMethylData1 - A matrix with DNA methylation levels from some CpGs on chromosome 1
  • brcaPCScores - A matrix with principal component scores for PCs 1-4 for four breast cancer patients.
  • brcaPCScores657 - A data.frame with principal component scores for PCs 1-4 for 657 breast cancer patients as well as a column with estrogen receptor status.
  • esr1_chr1 - Estrogen receptor alpha binding regions.
  • gata3_chr1 - Gata3 binding regions.
  • nrf1_chr1 - Nrf1 binding regions.
  • rsScores - Example COCOA Results

On BioConductor:COCOA-2.19.0(bioc 3.20)COCOA-2.18.0(bioc 3.19)

epigeneticsdnamethylationatacseqdnaseseqmethylseqmethylationarrayprincipalcomponentgenomicvariationgeneregulationgenomeannotationsystemsbiologyfunctionalgenomicschipseqsequencingimmunooncologydna-methylationpca

6.00 score 10 stars 20 scripts 220 downloads 14 exports 117 dependencies

Last updated 23 days agofrom:16ecf4b8d5. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 30 2024
R-4.5-winNOTEOct 30 2024
R-4.5-linuxNOTEOct 30 2024
R-4.4-winNOTEOct 30 2024
R-4.4-macNOTEOct 30 2024
R-4.3-winNOTEOct 30 2024
R-4.3-macNOTEOct 30 2024

Exports:aggregateSignalaggregateSignalGRListconvertToFromNullDistgetGammaPValgetMetaRegionProfilegetPermStatgetTopRegionsplotAnnoScoreDistregionQuantileByTargetVarrsRankingIndexrsScoreHeatmaprunCOCOArunCOCOAPermsignalAlongAxis

Dependencies:abindaskpassassortheadbeachmatBHBiobaseBiocGenericsBiocIOBiocParallelBiostringsbitopsBSgenomebsseqcirclizecliclueclustercodetoolscolorspaceComplexHeatmapcpp11crayoncurldata.tableDelayedArrayDelayedMatrixStatsdigestdoParalleldplyrfansifarverfitdistrplusforeachformatRfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataGenomicAlignmentsGenomicRangesGetoptLongggplot2GlobalOptionsgluegtablegtoolsHDF5ArrayhttrIRangesisobanditeratorsjsonlitelabelinglambda.rlatticelifecyclelimmalocfitmagrittrMASSMatrixMatrixGenericsmatrixStatsmgcvmimeMIRAmunsellnlmeopensslpermutepillarpkgconfigpngpurrrR.methodsS3R.ooR.utilsR6RColorBrewerRcppRCurlrestfulrrhdf5rhdf5filtersRhdf5libRhtslibrjsonrlangRsamtoolsrtracklayerS4ArraysS4VectorsscalesshapesimpleCachesnowSparseArraysparseMatrixStatsstatmodstringistringrSummarizedExperimentsurvivalsystibbletidyrtidyselectUCSC.utilsutf8vctrsviridisLitewithrXMLXVectoryamlzlibbioc

Introduction to Coordinate Covariation Analysis

John Lawson

Rendered fromIntroToCOCOA.Rmdusingknitr::rmarkdownon Oct 30 2024.

Last update: 2020-10-10
Started: 2018-10-25

Readme and manuals

Help Manual

Help pageTopics
Score a region set using feature contribution scoresaggregateSignal
Score many region setsaggregateSignalGRList
Atf3 binding regions.atf3_chr1
A GRanges object with coordinates for select BRCA ATAC-seq peak regions from chr1.brcaATACCoord1
A matrix with ATAC-seq counts in select peak regions from chromosome 1 for 37 patients.brcaATACData1
A GRanges object with genomic coordinates for cytosines from chr1 for the package's built-in DNA methylation databrcaMCoord1
A data.frame with patient metadata for breast cancer patients.brcaMetadata
A matrix with DNA methylation levels from some CpGs on chromosome 1brcaMethylData1
A matrix with principal component scores for PCs 1-4 for four breast cancer patients.brcaPCScores
A data.frame with principal component scores for PCs 1-4 for 657 breast cancer patients as well as a column with estrogen receptor status.brcaPCScores657
Coordinate Covariation Analysis (COCOA)COCOA
Converts COCOA permutation results to null distributions and vice versaconvertToFromNullDist
Estrogen receptor alpha binding regions.esr1_chr1
Gata3 binding regions.gata3_chr1
Get a p-value for region set scores based on a gamma distribution.getGammaPVal
Create a "meta-region" profilegetMetaRegionProfile
Get p-value or z-score based on permutation resultsgetPermStat
Get regions that are most associated with target variablegetTopRegions
Nrf1 binding regions.nrf1_chr1
Plot ranked region set scores, annotating groups of interestplotAnnoScoreDist
Visualize how individual regions are associated with target variableregionQuantileByTargetVar
Get indices for top scored region setsrsRankingIndex
Heatmap of region set scoresrsScoreHeatmap
Example COCOA Results (made up)rsScores
Run COCOA: quantify inter-sample variation, score region setsrunCOCOA
Run COCOA permutations to get p-valuesrunCOCOAPerm
Visualize how genomic signal in a region set changes along a given axissignalAlongAxis