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fCCAC

This is thereleased version of fCCAC; for the devel version, seefCCAC.

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

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DOI: 10.18129/B9.bioc.fCCAC


Bioconductor version: Release (3.22)

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 iD 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 appropriateBioconductor release.

Documentation

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

browseVignettes("fCCAC")
fCCAC VignettePDFR Script
Reference ManualPDF
NEWSText

Need some help? Ask on the Bioconductor Support site!

Details

biocViewsATACSeq,ChIPSeq,Coverage,Epigenetics,FunctionalGenomics,MNaseSeq,RNASeq,Sequencing,Software,Transcription
Version1.36.0
In Bioconductor sinceBioC 3.4 (R-3.3) (9 years)
LicenseArtistic-2.0
DependsR (>= 4.2.0),S4Vectors,IRanges,GenomicRanges, grid
Importsfda,RColorBrewer,genomation,ggplot2,ComplexHeatmap, grDevices, stats, utils
System Requirements
URLhttps://github.com/pmb59/fCCAC
Bug Reportshttps://github.com/pmb59/fCCAC/issues
See More
SuggestsRUnit,BiocGenerics,BiocStyle,knitr,rmarkdown
Linking To
Enhances
Depends On Me
Imports Me
Suggests Me
Links To Me
Build ReportBuild Report

Package Archives

FollowInstallation instructions to use this package in your R session.

Source PackagefCCAC_1.36.0.tar.gz
Windows Binary (x86_64) fCCAC_1.36.0.zip
macOS Binary (x86_64)fCCAC_1.36.0.tgz
macOS Binary (arm64)fCCAC_1.36.0.tgz
Source Repositorygit clone https://git.bioconductor.org/packages/fCCAC
Source Repository (Developer Access)git clone git@git.bioconductor.org:packages/fCCAC
Bioc Package Browserhttps://code.bioconductor.org/browse/fCCAC/
Package Short Urlhttps://bioconductor.org/packages/fCCAC/
Package Downloads ReportDownload Stats

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