analyzeIBDsegments: Loop over extracted IBD segments to supply a descriptive statistics

Description

analyzeIBDsegments: R implementation of analyzeIBDsegments.

The functions provides a loop over all detected IBD segments in order to compute descriptive statistics.

Usage

analyzeIBDsegments(fileName,runIndex="", annotPostfix="_annot.txt",startRun=1,endRun,shift=5000, intervalSize=10000)

Arguments

fileName

file name prefix without type of the result of hapFabia; Attention no type!

runIndex

a string that marks the output of this run if splitting the analysis into subsets of intervals defined by startRun and endRun.

annotPostfix

postfix string for the SNV annotation file.

startRun

first interval.

endRun

last interval.

shift

distance between start of adjacent intervals.

intervalSize

number of SNVs in an interval.

Value

startRun: first interval.
endRun: last interval.
noIBDsegments: number of IBD segments.
avIBDsegmentPos: vector of physical locations of IBD segments.
avIBDsegmentLengthSNV: vector of lengths of IBD segments given in number of SNVs.
avIBDsegmentLength: vector of lengths of IBD segments in bp.
avnoIndividp: vector of number of individuals that belong to the IBD segment.
avnoTagSNVs: vector of number of tagSNVs that mark the IBD segment.
avnoFreq: vector of minor allele frequencies of tagSNVs.
avnoGroupFreq: vector of minor allele frequencies within the considered subpopulation.
avnotagSNVChange: vector indicating a switch between minor and major alleles of tagSNVs (1=switched,0=not switched).
avnotagSNVsPerIndividual: vector of number of tagSNVs per individual.
avnoindividualPerTagSNV: vector of number of individuals that possess the minor allele per tagSNV .
avIBDsegmentPosS: summary statistics of physical locations of IBD segments.
avIBDsegmentLengthS: summary statistics of lengths of IBD segments.
avnoIndividS: summary statistics of number of individuals that belong to the IBD segment.
avnoTagSNVsS: summary statistics of number of tagSNVs that mark the IBD segment.
avnoFreqS: summary statistics of minor allele frequencies of tagSNVs.
avnoGroupFreqs: summary statistics of minor allele frequencies within the considered subpopulation.
avnotagSNVChangeS: summary statistics of vector that indicates a switch between minor and major alleles of tagSNVs (1=switched,0=not switched).
avnotagSNVsPerIndividualS: summary statistics of number of tagSNVs per individual.
avnoindividualPerTagSNVS: summary statistics of number of individuals that possess the minor allele per tagSNV.

Details

The functions provides a loop over all detected IBD segments in order to compute descriptive statistics. The loop goes over the intervals that have been analyzed for IBD segments by iterateIntervals. Duplicates are ignored at this analysis and must be identified in a preceding step via identifyDuplicates. Other statistics and annotations can be computed if the code is changed accordingly.

Implementation in R.

References

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

Examples

Run this code


## 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 detection
# 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 bps:")
# 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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