fCCAC-package: functional Canonical Correlation Analysis to evaluate...

fCCAC-packageR Documentation

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

Description

An application of functional canonical correlation analysis to assess covariance of nucleic acid sequencing datasets such as chromatin immunoprecipitation followed by deep sequencing (ChIP-seq).

Details

Package: fCCAC
Type: Package
Version: 1.23.1
Date: 2022-05-28
License: Artistic-2.0
LazyLoad: yes

Author(s)

Pedro Madrigal,

Maintainer: Pedro Madrigal pmadrigal@ebi.ac.uk

References

Madrigal P (2017) fCCAC: functional canonical correlation analysis to evaluate covariance between nucleic acid sequencing datasets. Bioinformatics: http://doi.org/10.1093/bioinformatics/btw724.

Examples


## hg19. chr21:40000000-48129895 H3K4me3 data from Bertero et al. (2015)
    if (.Platform$OS.type == "unix") {
  
        owd <- setwd(tempdir())

        bigwig1 <- "chr21_H3K4me3_1.bw"
        bigwig2 <- "chr21_H3K4me3_2.bw"
        bigwig3 <- "chr21_H3K4me3_3.bw"
        peakFile <- "chr21_merged_ACT_K4.bed"
        labels <- c( "H3K4me3", "H3K4me3","H3K4me3" )
        ti <- "H3K4me3 peaks"

        r1 <- system.file("extdata", bigwig1,  package="fCCAC",mustWork = TRUE)
        r2 <- system.file("extdata", bigwig2,  package="fCCAC",mustWork = TRUE)
        r3 <- system.file("extdata", bigwig3,  package="fCCAC",mustWork = TRUE)
        r4 <- system.file("extdata", peakFile, package="fCCAC",mustWork = TRUE)

        fc <- fccac(bar=NULL, main=ti, peaks=r4, bigwigs=c(r1,r2,r3), labels=labels, splines=15, nbins=100, ncan=15) 

        head(fc)

        setwd(owd)
    }

pmb59/fCCAC documentation built on May 31, 2022, 4:38 a.m.