compareIBDsegmentLists: Hierarchical clustering of IBD segments stored in IBD segment...
In hapFabia: hapFabia: Identification of very short segments of identity by descent (IBD) characterized by rare variants in large sequencing data

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

compareIBDsegmentLists: R implementation of compareIBDsegmentLists.

The IBD segments in one or two list(s) are compared by hierarchical clustering. Different similarity measures are available. Called by hapFabia.

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## S4 method for signature 
## 'IBDsegmentList,ANY,character,ANY,ANY,numeric,numeric'
compareIBDsegmentLists(IBDsegmentList1,IBDsegmentList2=NULL,simv="minD",pTagSNVs=NULL,pIndivid=NULL,minTagSNVs=6,minIndivid=2)

`IBDsegmentList1`	list of IBD segments given as `IBDsegmentList` object.
`IBDsegmentList2`	optional: second list of IBD segments given as `IBDsegmentList` object.
`simv`	similarity measure: `minD` (percentage of the smaller set explained by the larger set), `jaccard` (Jaccard index), `dice` (Dice index), or `maxD` (percentage of the larger set explained by the smaller set); default `minD`.
`pTagSNVs`	optional: exponent for tagSNV similarity.
`pIndivid`	optional: exponent for individuals similarity.
`minTagSNVs`	required minimal number of overlapping SNVs to assign similarity different from zero; default 6.
`minIndivid`	required minimal number of overlapping individuals to assign similarity different from zero; default 2.

Similarities are separately computed for SNVs and for individuals using one of the similarity measure: "minD" (percentage of the smaller set explained by the larger set), "jaccard" (Jaccard index), "dice" (Dice index), or "maxD" (percentage of the larger set explained by the smaller set). One minus the product between SNV similarity and individuals similarity is the final value used for clustering.

The final similarity measure is not a distance but is symmetric, one for similarity of an IBD segment with itself, zero if either CNVs or individuals have no overlap, and between zero and one. Called by hapFabia.

Implementation in R.

clust

object of class hclust which describes the tree produced by the hierarchical clustering method.

Sepp Hochreiter

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

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

data(hapRes)
IBDsegmentList1 <- hapRes$IBDsegmentList1
IBDsegmentList2 <- hapRes$IBDsegmentList2
comp <-
compareIBDsegmentLists(IBDsegmentList1,
   IBDsegmentList2,simv="minD",pTagSNVs=NULL,
   pIndivid=NULL,minTagSNVs=6,minIndivid=2)

show(comp)