calcKL: Calculate the Kullback-Leibler Divergence Between the k-mer...
In vsbuffalo/qrqc: Quick Read Quality Control

Description Usage Arguments Value Note Author(s) See Also Examples

calcKL takes in an object that inherits from SequenceSummary that has a kmers slot, and returns the terms of the K-L divergence sum (which correspond to items in the sample space, in this case, k-mers).

  calcKL(x)

`x`	an S4 object a class that inherits from `SequenceSummary`.

calcKL returns a data.frame with columns:

`kmer`	the k-mer sequence.
`position`	the position in the read.
`kl`	the K-L term for this k-mer in the K-L sum, calculated as p(i)*log2(p(i)/q(i)).
`p`	the probability for this k-mer, at this position.
`q`	the probability for this k-mer across all positions.

The K-L divergence calculation in calcKL uses base 2 in the log; the units are in bits.

Vince Buffalo <vsbuffalo@ucdavis.edu>

kmerKLPlot, getKmer

  ## Load a somewhat contaminated FASTQ file
  s.fastq <- readSeqFile(system.file('extdata', 'test.fastq',
    package='qrqc'), hash.prop=1)

  ## As with getQual, this function is provided so custom graphics can
  ## be made easily. For example K-L divergence by position:
  kld <- with(calcKL(s.fastq), aggregate(kl, list(position),
    sum))
  colnames(kld) <- c("position", "KL")
  p <- ggplot(kld) + geom_line(aes(x=position, y=KL), color="blue")
  p + scale_y_continuous("K-L divergence")