findDenseRegions: Find accumulations of values via histogram counts

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/hapFabia.R

Description

findDenseRegions: R implementation of findDenseRegions.

Extracts histogram bins which counts are larger than a threshold. Only values larger than a given quantile are considered.

Usage

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findDenseRegions(obs,p=0.9,inte=500,thres=11,off=0)

Arguments

obs

values for constructing the histogram.

p

quantile above which the values of obs are included into the histogram.

inte

size of the histogram bins.

thres

threshold for histogram counts: bin with counts larger equal the threshold are selected.

off

offset of the histogram bin positions.

Details

Extracts histogram bins which counts are larger than a threshold. The threshold is supplied and can be computed according to some assumptions on expected bin counts. Only values larger than a given quantile are considered.

Implementation in R.

Value

list with

m

vector of locations of the selected bin (middle of bins).

l

vector of lengths of the bins.

pos

list where each element is a vector of locations of values that contributed to the counts (SNV positions).

len

vector of counts or equivalently vector of the number of SNVs.

Author(s)

Sepp Hochreiter

References

S. Hochreiter et al., ‘FABIA: Factor Analysis for Bicluster Acquisition’, Bioinformatics 26(12):1520-1527, 2010.

See Also

IBDsegment-class, IBDsegmentList-class, analyzeIBDsegments, compareIBDsegmentLists, extractIBDsegments, findDenseRegions, hapFabia, hapFabiaVersion, hapRes, chr1ASW1000G, IBDsegmentList2excel, identifyDuplicates, iterateIntervals, makePipelineFile, matrixPlot, mergeIBDsegmentLists, mergedIBDsegmentList, plotIBDsegment, res, setAnnotation, setStatistics, sim, simu, simulateIBDsegmentsFabia, simulateIBDsegments, split_sparse_matrix, toolsFactorizationClass, vcftoFABIA

Examples

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data(res)
ib <- findDenseRegions(L(res)[,1],p=0.9,
   inte=50,thres=6,off=0)
print(ib$len)

hapFabia documentation built on Nov. 8, 2020, 5:17 p.m.