identifyDuplicates {hapFabia} | R Documentation

## Identify duplicates of IBD segments

### Description

`identifyDuplicates`: R implementation of `identifyDuplicates`.

IBD segments that are similar to each other are identified. This function is in combination with `split_sparse_matrix` whith splits a chromosome in overlapping intervals. These intervals are analyzed by `iterateIntervals` for IBD segments. Now, these IBD segments are checked for duplicates by `identifyDuplicates`. Results are written to the file "dups.Rda".

### Usage

    identifyDuplicates(fileName,startRun=1,endRun,
       shift=5000,intervalSize=10000)

### Arguments

`fileName` | file name prefix without type of the result of `hapFabia`; Attention no type!
`startRun` | first interval.
`endRun` | last interval.
`shift` | distance between start of adjacent intervals.
`intervalSize` | number of SNVs in a interval.

### Details

IBD segments that are similar to each other are identified and the result is written to the file "dups.Rda". For analysis across a whole chromosome this information is important in order to avoid multiple counting of features from the same IBD segment. Used subsequently to `iterateIntervals` which analyzes intervals of a chromosome for IBD segments. The information on duplicates (or similar IBD segments) is important for a subsequent run of `analyzeIBDsegments` to avoid redundancies.

Results are saved in "dups.Rda" which contains

1. `dups` (the index of duplicates),

2. `un` (the index of non-duplicates),

3. `countsA1` (the counts and mapping to intervals for non-duplicates), and

4. `countsA2` (the counts and mapping to intervals for all IBD segments).

Implementation in R.

### Value

IBD segments that are similar to each other are identified

### 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

    print("Identify duplicates of IBD segments")
    ## Not run:
    #########################################
    ## Already run in "iterateIntervals.Rd" ##
    #########################################

    #Work in a temporary directory.

    old_dir <- getwd()
    setwd(tempdir())

    # Load data and write to vcf file.
    data(chr1ASW1000G)
    write(chr1ASW1000G,file="chr1ASW1000G.vcf")

    #Create the analysis pipeline for extracting IBD segments
    makePipelineFile(fileName="chr1ASW1000G",shiftSize=500,intervalSize=1000,haplotypes=TRUE)

    source("pipeline.R")

    # Following files are produced:
    list.files(pattern="chr1")

    # Next we load interval 5 and there the first and second IBD segment
    posAll <- 5
    start <- (posAll-1)*shiftSize
    end <- start + intervalSize
    pRange <- paste("_",format(start,scientific=FALSE),"_",format(end,scientific=FALSE),sep="")
    load(file=paste(fileName,pRange,"_resAnno",".Rda",sep=""))
    IBDsegmentList <- resHapFabia$mergedIBDsegmentList
    summary(IBDsegmentList)
    IBDsegment1 <- IBDsegmentList[[1]]
    summary(IBDsegment1)
    IBDsegment2 <- IBDsegmentList[[2]]
    summary(IBDsegment2)

    #Plot the first IBD segment in interval 5
    plot(IBDsegment1,filename=paste(fileName,pRange,"_mat",sep=""))

    #Plot the second IBD segment in interval 5
    plot(IBDsegment2,filename=paste(fileName,pRange,"_mat",sep=""))

    setwd(old_dir)

    ## End(Not run)

    ## Not run:
    ###here an example of the the automatically generated pipeline
    ### with: shiftSize=5000,intervalSize=10000,fileName="filename"

    #####define intervals, overlap, filename #######
    shiftSize <- 5000
    intervalSize <- 10000
    fileName="filename" # without type
    haplotypes <- TRUE
    dosage <- FALSE

    #####load library#######
    library(hapFabia)

    #####convert from .vcf to _mat.txt#######
    vcftoFABIA(fileName=fileName)

    #####copy haplotype, genotype, or dosage matrix to matrix#######
    if (haplotypes) {
        file.copy(paste(fileName,"_matH.txt",sep=""), paste(fileName,"_mat.txt",sep=""))
    } else {
        if (dosage) {
            file.copy(paste(fileName,"_matD.txt",sep=""), paste(fileName,"_mat.txt",sep=""))
        } else {
            file.copy(paste(fileName,"_matG.txt",sep=""), paste(fileName,"_mat.txt",sep=""))
        }
    }

    #####split/ generate intervals#######
    split_sparse_matrix(fileName=fileName,intervalSize=intervalSize,
    shiftSize=shiftSize,annotation=TRUE)

    #####compute how many intervals we have#######
    ina <- as.numeric(readLines(paste(fileName,"_mat.txt",sep=""),n=2))
    noSNVs <- ina[2]
    over <- intervalSize%/%shiftSize
    N1 <- noSNVs%/%shiftSize
    endRunA <- (N1-over+2)

    #####analyze each interval#######
    #####may be done by parallel runs#######
    iterateIntervals(startRun=1,endRun=endRunA,shift=shiftSize,
    intervalSize=intervalSize,fileName=fileName,individuals=0,
    upperBP=0.05,p=10,iter=40,alpha=0.03,cyc=50,IBDsegmentLength=50,
    Lt = 0.1,Zt = 0.2,thresCount=1e-5,mintagSNVsFactor=3/4,
    pMAF=0.03,haplotypes=haplotypes,cut=0.8,procMinIndivids=0.1,thresPrune=1e-3,
    simv="minD",minTagSNVs=6,minIndivid=2,avSNVsDist=100,SNVclusterLength=100)

    #####identify duplicates#######
    identifyDuplicates(fileName=fileName,startRun=1,endRun=endRunA,
    shift=shiftSize,intervalSize=intervalSize)

    #####analyze results; parallel#######
    anaRes <- analyzeIBDsegments(fileName=fileName,startRun=1,endRun=endRunA,
    shift=shiftSize,intervalSize=intervalSize)
    print("Number IBD segments:")
    print(anaRes$noIBDsegments)
    print("Statistics on IBD segment length in SNVs (all SNVs in the IBD segment):")
    print(anaRes$avIBDsegmentLengthSNVS)
    print("Statistics on IBD segment length in bp:")
    print(anaRes$avIBDsegmentLengthS)
    print("Statistics on number of individuals belonging to IBD segments:")
    print(anaRes$avnoIndividS)
    print("Statistics on number of tagSNVs of IBD segments:")
    print(anaRes$avnoTagSNVsS)
    print("Statistics on MAF of tagSNVs of IBD segments:")
    print(anaRes$avnoFreqS)
    print("Statistics on MAF within the group of tagSNVs of IBD segments:")
    print(anaRes$avnoGroupFreqS)
    print("Statistics on number of changes between major and minor allele frequency:")
    print(anaRes$avnotagSNVChangeS)
    print("Statistics on number of tagSNVs per individual of an IBD segment:")
    print(anaRes$avnotagSNVsPerIndividualS)
    print("Statistics on number of individuals that have the minor allele of tagSNVs:")
    print(anaRes$avnoindividualPerTagSNVS)

    #####load result for interval 50#######
    posAll <- 50 # (50-1)*5000 = 245000: interval 245000 to 255000
    start <- (posAll-1)*shiftSize
    end <- start + intervalSize
    pRange <- paste("_",format(start,scientific=FALSE),"_",
    format(end,scientific=FALSE),sep="")
    load(file=paste(fileName,pRange,"_resAnno",".Rda",sep=""))
    IBDsegmentList <- resHapFabia$mergedIBDsegmentList # $

    summary(IBDsegmentList)
    #####plot IBD segments in interval 50#######
    plot(IBDsegmentList,filename=paste(fileName,pRange,"_mat",sep=""))
       ##attention: filename without type ".txt"

    #####plot the first IBD segment in interval 50#######

    IBDsegment <- IBDsegmentList[[1]]
    plot(IBDsegment,filename=paste(fileName,pRange,"_mat",sep=""))
       ##attention: filename without type ".txt"

    ## End(Not run)

[Package hapFabia version 1.29.0 Index]