Converting genotyping data from vcf to sparse matrix format

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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

1
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.

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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## 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)

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