fCCAC
This is the released version of fCCAC; for the devel version, see fCCAC.
All Bioconductor versions of fCCAC
3.24 (devel), 3.23 (release), 3.22, 3.21, 3.20, 3.19, 3.18, 3.17, 3.16, 3.15, 3.14, 3.13, 3.12, 3.11, 3.10, 3.9, 3.8, 3.7, 3.6, 3.5, 3.4
functional Canonical Correlation Analysis to evaluate Covariance between nucleic acid sequencing datasets
Bioconductor version: 3.23 · Package version: 1.38.0
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"):
Pedro Madrigal. fCCAC: functional Canonical Correlation Analysis to evaluate Covariance between nucleic acid sequencing datasets. doi:10.18129/B9.bioc.fCCAC, R package version 1.38.0, https://bioconductor.org/packages/fCCAC.
Generated from the package metadata; it may differ from the package's own citation.
Installation
To install this package, start R (version "4.6") 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.
Details
| Version | 1.38.0 |
| License | Artistic-2.0 |
| URL | https://github.com/pmb59/fCCAC |
| Bug Reports | https://github.com/pmb59/fCCAC/issues |
| Last updated | 2026-04-28 |
| In Bioconductor since | BioC 3.4 (R-3.3) (9 years) |
| Downloads rank | 789 of 2,418 |
| Source branch | RELEASE_3_23 |
| Build report | Bioconductor build system, r-universe |
| biocViews | ATACSeq, ChIPSeq, Coverage, Epigenetics, FunctionalGenomics, MNaseSeq, RNASeq, Sequencing, Software, Transcription |
| Package Short Url | https://bioconductor.org/packages/fCCAC/ |
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("fCCAC")| fCCAC Vignette | R Script | |
| Reference Manual | ||
| NEWS | Text |
Download
Follow the installation instructions to use this package in your R session.
| Source package | fCCAC_1.38.0.tar.gz |
| Windows binary (x86_64) | fCCAC_1.38.0.zip |
| macOS binary (arm64) | fCCAC_1.38.0.tgz |
| macOS binary (x86_64) | fCCAC_1.38.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/fCCAC |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/fCCAC |
| Package Downloads Report | Download Stats |
Dependencies
Depends: R (>= 4.2.0), S4Vectors, IRanges, GenomicRanges, grid
Imports: fda, RColorBrewer, genomation, ggplot2, ComplexHeatmap, grDevices, stats, utils
Suggests: RUnit, BiocGenerics, BiocStyle, knitr, rmarkdown