plotHistDists: plot MMD distances
In MMDiff: Statistical Testing for ChIP-Seq data sets

Description Usage Arguments Author(s) See Also Examples

the generated plots are similar to MA plots, except that the computed distances (MMD) are shown on the y-axes instead of log fold change.

plotHistDists(DBA, method = "MMD", group1, group2, 
              field4X = "NormTotalCounts", bUsePval = FALSE,
              pnames = "combined", thresh = 0.05, 
              save2file = FALSE, fn.pics,  ftype = pdf,
              xlim = NULL, ylim = NULL)

`DBA`	DBA object, after running compHistDists.
`method`	specify method used to determine distances between histograms (could be MMD, GMD or Pearson).
`group1`	sample ids of control group
`group2`	sample ids of treatment group
`field4X`	name of list element in DBA$MD that is used for pooling of peaks. (e.g. NormTotalCounts or RawTotalCounts)
`bUsePval`	logical indicating whether to use FDR (FALSE) or p-value (TRUE) for thresholding.
`pnames`	name of comparison used to generated p-values, eg. name1 vs name2
`thresh`	threshold to show significant peaks. (e.g. < 0.05)
`save2file`	if TRUE plot is saved to pdf file
`fn.pics`	file name, where the plot should be saved to.
`ftype`	file format for saving the plot (pdf, postcsript, png)
`xlim`	the x limits (x1, x2) of the plot. The default value, 'NULL', indicates that the range of the finite values to be plotted should be used.
`ylim`	the y limits of the plot.

Gabriele Schweikert

getPeakProfiles, getNormFactors, compHistDists, detPeakPvals

# load DBA objects with peak profiles and pairwise distances
data(Cfp1Dists)

# determine empirical p-values:
group1 <- c("WT.AB2", "Resc.AB2")
group2 <- c("Null.AB2")
Cfp1Pvals <- detPeakPvals(Cfp1Dists, group1=group1, group2=group2,
             name1='Wt/Resc', name2='Null')

# plot distances and peaks which are significantly different:

plotHistDists(Cfp1Pvals, group1=group1, group2=group2)