vcftoFABIA {hapFabia} | R Documentation

## Converting genotyping data from `vcf` to sparse matrix format

### Description

`vcftoFABIA`: C implementation with an R wrapper of `vcftoFABIA`.

Converts files giving the genotype in vcf format to sparse matrix formats as used by FABIA. Phased and unphased genotypes as well as dosages or likelihoods are written to files in sparse matrix formats. Haplotype data is stored in `fileName_matH.txt`, genotype data in `fileName_matG.txt`, and dosage data in `fileName_matD.txt`.

SNV annotations are stored in `fileName_annot.txt` and the names of the individuals in `fileName_individuals.txt`. These files serve as input for `split_sparse_matrix`.

### Usage

    vcftoFABIA(fileName,prefixPath="",noSnvs=NULL,outputFile=NULL)

### Arguments

`fileName` | string giving the file name without the file type '.vcf'. Attention: remove file type!
`prefixPath` | path to the file.
`noSnvs` | optional: the number of SNVs; needed for memory allocation; if not known it is determined by first reading all lines of the file.
`outputFile` | optional: prefix for the output files, if not given then the input file prefix is used.

### Details

The function `vcftoFABIA` converts `fileName.vcf` to sparse matrix format giving (if not outputFile is given then Outfilename=fileName):

1. `Outfilename_matH.txt` (haplotype data),

2. `Outfilename_matG.txt` (genotype data),

3. `Outfilename_matD.txt` (dosage data),

together with the SNV annotation file and individual's label file:

1. `Outfilename_annot.txt` and

2. `Outfilename_individuals.txt`.

In a subsequent step these files can be split into intervals by `split_sparse_matrix` and thereafter IBD segments extracted by `iterateIntervals`.

Implementation in C. Also command line programs are supplied.

### Value

Converting genotyping data from vcf to sparse matrix format

### 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

    ## 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 IBD segment extraction
    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]