fCCAC

functional Canonical Correlation Analysis to evaluate Covariance between nucleic acid sequencing datasets

Bioconductor version: Release (3.19)

Computational evaluation of variability across DNA or RNA sequencing datasets is a crucial step in genomics, as it allows both to evaluate reproducibility of replicates, and to compare different datasets to identify potential correlations. fCCAC applies functional Canonical Correlation Analysis to allow the assessment of: (i) reproducibility of biological or technical replicates, analyzing their shared covariance in higher order components; and (ii) the associations between different datasets. fCCAC represents a more sophisticated approach that complements Pearson correlation of genomic coverage.

Author: Pedro Madrigal [aut, cre]

Maintainer: Pedro Madrigal <pmadrigal at ebi.ac.uk>

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

Installation

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


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("fCCAC")

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

Documentation

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

browseVignettes("fCCAC")

fCCAC Vignette	PDF	R Script
Reference Manual	PDF
NEWS	Text

Need some help? Ask on the Bioconductor Support site!

Details

biocViews	ATACSeq, ChIPSeq, Coverage, Epigenetics, FunctionalGenomics, MNaseSeq, RNASeq, Sequencing, Software, Transcription
Version	1.30.0
In Bioconductor since	BioC 3.4 (R-3.3) (8 years)
License	Artistic-2.0
Depends	R (>= 4.2.0), S4Vectors, IRanges, GenomicRanges, grid
Imports	fda, RColorBrewer, genomation, ggplot2, ComplexHeatmap, grDevices, stats, utils
System Requirements
URL

Suggests	RUnit, BiocGenerics, BiocStyle, knitr, rmarkdown
Linking To
Enhances
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report	Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package	fCCAC_1.30.0.tar.gz
Windows Binary (x86_64)	fCCAC_1.30.0.zip (64-bit only)
macOS Binary (x86_64)	fCCAC_1.30.0.tgz
macOS Binary (arm64)	fCCAC_1.30.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/fCCAC
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/fCCAC
Bioc Package Browser	https://code.bioconductor.org/browse/fCCAC/
Package Short Url	https://bioconductor.org/packages/fCCAC/
Package Downloads Report	Download Stats