DOI: 10.18129/B9.bioc.fCCAC  

This package is for version 3.17 of Bioconductor; for the stable, up-to-date release version, see fCCAC.

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

Bioconductor version: 3.17

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>

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biocViews ATACSeq, ChIPSeq, Coverage, Epigenetics, FunctionalGenomics, MNaseSeq, RNASeq, Sequencing, Software, Transcription
Version 1.26.0
In Bioconductor since BioC 3.4 (R-3.3) (7 years)
License Artistic-2.0
Depends R (>= 4.2.0), S4Vectors, IRanges, GenomicRanges, grid
Imports fda, RColorBrewer, genomation, ggplot2, ComplexHeatmap, grDevices, stats, utils
Suggests RUnit, BiocGenerics, BiocStyle, knitr, rmarkdown
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