This is the released version of fCCAC; for the devel version, see fCCAC.
functional Canonical Correlation Analysis to evaluate Covariance between nucleic acid sequencing datasetsBioconductor version: Release (3.21)
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] ORCID: 0000-0003-1959-8199
Maintainer: Pedro Madrigal <pmadrigal at ebi.ac.uk>
Citation (from within R, entercitation("fCCAC")): Installation
To install this package, start R (version "4.5") 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.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("fCCAC")Follow Installation instructions to use this package in your R session.
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