pmb59/fCCAC: functional Canonical Correlation Analysis to evaluate Covariance between nucleic acid sequencing datasets

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.

Getting started

Package details

Bioconductor views ATACSeq ChIPSeq Coverage Epigenetics FunctionalGenomics MNaseSeq RNASeq Sequencing Transcription
Maintainer
LicenseArtistic-2.0
Version1.23.1
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("pmb59/fCCAC")
pmb59/fCCAC documentation built on May 31, 2022, 4:38 a.m.