fCCAC-package | R Documentation |
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).
Package: | fCCAC |
Type: | Package |
Version: | 1.23.1 |
Date: | 2022-05-28 |
License: | Artistic-2.0 |
LazyLoad: | yes |
Pedro Madrigal,
Maintainer: Pedro Madrigal pmadrigal@ebi.ac.uk
Madrigal P (2017) fCCAC: functional canonical correlation analysis to evaluate covariance between nucleic acid sequencing datasets. Bioinformatics: http://doi.org/10.1093/bioinformatics/btw724.
## 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) }
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