detPeakPvals: Compute p-values for each peak based on distances between...
In MMDiff: Statistical Testing for ChIP-Seq data sets

Description Usage Arguments Value Author(s) See Also Examples

Compute p-values for each peak based on distances between histograms, contrasting group1 (e.g. control samples) with group2 (e.g. treatment samples). To estimate within group distances and between group distances peaks are pooled according to their mean (normalized) total counts. p-values are adjusted for multiple testing using the method by Benjamini & Hochberg (1995).

detPeakPvals(DBA, method = "MMD", group1, group2,
             name1 = "g1", name2 = "g2", Usefiltered = TRUE,
             PeakIDs = NULL,
             quantprobs = seq(0, 1,0.05),
             fieldName = "NormTotalCounts",bNormWidth=FALSE,
             bSampleMean = FALSE, overWrite =  FALSE)

`DBA`	DBA object, after running getPeakProfiles and compHistDists.
`method`	which distance method should be used. (can be 'MMD','GMD' or 'Pearson')
`group1`	sample ids of control group
`group2`	sample ids of treatment group
`name1`	name of control group
`name2`	name of treatment group
`Usefiltered`	If TRUE, only peaks that have passed the filter to detect Outliers are used. findOutlier must be run first, otherwise all peaks are used
`PeakIDs`	specify a subset of peaks which should be used for pooling (for example if outliers with extreme counts should be excluded)
`quantprobs`	numeric vector of probabilities with values in [0,1], used to specify which peaks are pooled together to estimate variances.
`fieldName`	name of list element in DBA$MD that is used for pooling of peaks. (e.g. NormTotalCounts or RawTotalCounts)
`bNormWidth`	logical indicating if counts should be normalized by peak width
`bSampleMean`	If true counts are averaged across all samples. Otherwise means are computed for each group separately.
`overWrite`	if TRUE, previous computed p-values are overwritten

DBA object, with additional element Pvals added to MD. Pvals again contains a list element named according to method applied (MMD). e.g. DBA$MD$Pvals$MMD This element is a matrix (nPeaks x ncomps) containing p-values for each peak and given comparison (group1 vs. group2). New comparisons (i.e. re-running detPeakPvals with different groups) are appended to the matrix.

Gabriele Schweikert

getPeakProfiles, getNormFactors, compHistDists, plotHistDists, plotPeak

## Not run: 
# load DBA objects with peak profiles and pairwise distances
data(Cfp1Dists)

# specify controll and treatment groups:
group1 <- c("WT.AB2", "Resc.AB2")
group2 <- c("Null.AB2")

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

# to plot distances and peaks which are significantly different use the
# plotHistDists function:

plotHistDists(Cfp1Pvals, group1=group1, group2=group2) 
## End(Not run)