plot.gc {cobindR} | R Documentation

## function to visualize GC content or CpG content of input sequences

### Description

plot.gc calculates the GC (or CpG) content based on a window size for each sequence and plots the content for all sequences as a heatmap over position and sequence.

### Usage

    ## S4 method for signature 'cobindr'
    plot.gc(x, seq.ids, cpg = F, wind.size = 50,
    sig.test = F, hm.margin = c(4, 10), frac = 10, n.cpu = NA)

### Arguments

`x` | an object of the class "cobindr", which will hold all necessary information about the sequences.
`seq.ids` | list of sequence identifiers, for which the GC (or CpG) content will be plotted.
`cpg` | logical flag, if cpg=TRUE the CpG content rather than the GC content will be calculated and plotted.
`wind.size` | integer describing the window size for GC content calculation
`sig.test` | logical flag, if sig.test=TRUE wilcoxon.test is performed per individual window against all windows in other sequence at the same position. The significance test might be slow for large number of sequences
`hm.margin` | optional argument providing the margin widths for the heatmap (if sig.test=FALSE)
`frac` | determines the overlap between consecutive windows as fraction wind.size/frac
`n.cpu` | number of CPUs to be used for parallelization. Default value is 'NA' in which case the number of available CPUs is checked and than used.

### Author(s)

Robert Lehmann <r.lehmann@biologie.hu-berlin.de>

### See Also

`testCpG`

### Examples

    library(Biostrings)

    n <- 50 # number of input sequences
    l <- 100 # length of sequences
    bases <- c("A","C","G","T") # alphabet
    # generate random input sequences with two groups with differing GC content
    seqs <- sapply(1:(3*n/4), function(x) paste(sample(bases, l, replace=TRUE,
    		prob=c(.3,.22,.2,.28)), collapse=""))
    seqs <- append(seqs, sapply(1:(n/4), function(x) paste(sample(bases, l,
    		replace=TRUE, prob=c(.25,.25,.25,.25)), collapse="")))
    #save sample sequences in fasta file
    tmp.file <- tempfile(pattern = "cobindr_sample_seq", tmpdir = tempdir(),
    fileext = ".fasta")
    writeXStringSet(DNAStringSet(seqs), tmp.file)

    cfg <- new('configuration')
    slot(cfg, 'sequence_type') <- 'fasta'
    slot(cfg, 'sequence_source') <- tmp.file
    # avoid complaint of validation mechanism
    slot(cfg, 'pfm_path') <- system.file('extdata/pfms',package='cobindR')
    slot(cfg, 'pairs') <- ''

    runObj <- new('cobindr', cfg, 'test')

    plot.gc(runObj, cpg = TRUE)

    unlink(tmp.file)

[Package cobindR version 1.18.0 Index]