identifyDuplicates {hapFabia} | R Documentation |
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".
identifyDuplicates(fileName,startRun=1,endRun, shift=5000,intervalSize=10000)
fileName |
file name prefix without type of the result of |
startRun |
first interval. |
endRun |
last interval. |
shift |
distance between start of adjacent intervals. |
intervalSize |
number of SNVs in a interval. |
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
dups
(the index of duplicates),
un
(the index of non-duplicates),
countsA1
(the counts and mapping to intervals for non-duplicates), and
countsA2
(the counts and mapping to intervals for all IBD segments).
Implementation in R.
IBD segments that are similar to each other are identified
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
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)