| heatmapfCCAC | R Documentation | 
Heatmap of F values obtained by Canonical Correlation Analysis. This function can only be used if all pairwise comparisons were computed previously with the function 'fccac', i.e., using "tf=c()".
  heatmapfCCAC(fc)
| fc | Output of the function 'fccac'. | 
Plots a Heatmap of F values using the package 'ComplexHeatmap'.
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.
fccac 
  ## 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" )
    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)
    ti <- "H3K4me3 peaks"
    fc <- fccac(bar=NULL, main=ti, peaks=r4, bigwigs=c(r1,r2,r3), labels=labels, splines=15, nbins=100, ncan=15) 
    head(fc)
    heatmapfCCAC(fc)
    setwd(owd)
    
  }
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