R/checkGenotypeFile.R

In GWASTools: Tools for Genome Wide Association Studies

checkGenotypeFile <- function(path=".",
                              filename, 
                              file.type=c("gds", "ncdf"),
                              snp.annotation, 
                              scan.annotation, 
                              sep.type,
                              skip.num,
                              col.total,
                              col.nums,
                              scan.name.in.file, 
                              check.scan.index,
                              n.scans.loaded,
                              allele.coding = c("AB", "nucleotide"),
                              diagnostics.filename = "checkGenotypeFile.diagnostics.RData",
                              verbose = TRUE) {
    
    ## sx is vector of sample indices to check
    ## N is the number of samples loaded so far

    if(!all(is.element(check.scan.index,1:n.scans.loaded))) stop("check.scan.index must be included in 1:n.scans.loaded")

    file.type <- match.arg(file.type)
    allele.coding <- match.arg(allele.coding)

    if (file.type == "gds") {
        genofile <- GdsGenotypeReader(filename)
    } else if (file.type == "ncdf") {
        genofile <- NcdfGenotypeReader(filename)
    }

    ## get sample and snp ids
    geno.sampid <- getScanID(genofile, index=1:n.scans.loaded)
    nc.snpid <- getSnpID(genofile)
    
    ## get sample info and file names
    stopifnot(all(c("scanID", "scanName", "file") %in% names(scan.annotation)))
    
    if(any(!is.element(geno.sampid, scan.annotation$scanID))) stop("some sample id(s) in ncdf file not found in sample annotation dataframe")
    scan.annotation <- scan.annotation[match(geno.sampid, scan.annotation$scanID),]
    files <- file.path(path, scan.annotation$file)

    ## check col.nums vector
    col.nums <- col.nums[!is.na(col.nums)]
    intensity.vars <-  c("quality", "X", "Y", "rawX", "rawY", "R", "Theta", "BAlleleFreq","LogRRatio")
    if(!all(names(col.nums) %in% c("snp", "sample", "geno", "a1", "a2", intensity.vars))) stop("problem with col.nums vector names")
    if(!is.integer(col.nums)) stop("col.nums vector class is not integer")
    if(!("snp" %in% names(col.nums))) stop("snp id missing in col.nums")
    if( max(col.nums) > col.total) stop("some element of col.nums is greater than total number of columns")
    
    ## check snp.annotation
    stopifnot(all(c("snpID", "snpName") %in% names(snp.annotation)))
    if(any(snp.annotation$snpID != sort(snp.annotation$snpID))) stop("snp annotation ids not in order")
    if(any(snp.annotation$snpID != nc.snpid)) stop("snp annotation ids not the same as in ncdf")
    n <- nrow(snp.annotation)
    
    ##generate colClasses vector for read.table
    cc <- rep("NULL",col.total)
    cc[col.nums[names(col.nums) %in% c("snp","sample","geno","a1","a2")]] <- "character"
    
    ##generate names for the genotype data.frame
    df.names <- names(sort(col.nums))
    
    ## set up objects to keep track of things for each file

    ## repeat diagnostics from when the ncdf was created
    fn <- length(files)
    read.file <- rep(NA, fn)  # keeps track of whether the file was readable or not
    row.num <- rep(NA, fn)	  # number of rows read
    sample.names <- vector("list",fn)		 # list of vectors of unique sample names in each file
    sample.match <- rep(NA, fn)		# indicator whether sample name inside file matches sample names in sample annotation data.frame
    missg <- vector("list",fn)		 # vector of character string(s) used for missing genotypes (i.e. not AA, AB or BB)
    snp.chk <- rep(NA,fn)
    chk <- rep(NA,fn)			# final check on data ready to load into ncdf

    ## new diagnostics
    ## snp.order <- rep(NA,fn)
    geno.chk <- rep(NA,fn)

    if(is.null(end)) end <- nscan(genofile)

    nsx <- length(check.scan.index)

    if (verbose) start <- Sys.time()	# to keep track of the rate of file processing
    for(i in check.scan.index){


        ## save at each iteration in case of crash
        diagnostics <- list(read.file, row.num, sample.names, sample.match, missg, snp.chk, chk, geno.chk)
        names(diagnostics) <- c("read.file", "row.num", "sample.names", "sample.match", "missg", "snp.chk", "chk",
                                "geno.chk")
        save(diagnostics, file=diagnostics.filename)

        ##read in the file for one sample and keep columns of interest; skip to next file if there is a read error (using function "try")
        if(scan.name.in.file==-1) {skip.num <- skip.num-1; head<-TRUE} else  {head<-FALSE}
        dat <- try(fread(files[i], header=head, sep=sep.type, skip=skip.num, colClasses=cc, data.table=FALSE))
        if (inherits(dat, "try-error")) { read.file[i] <- 0; message(paste("error reading file",i)); next } 		
        read.file[i] <- 1 
        ## get sample name from column heading for Affy
        if(scan.name.in.file==-1) {tmp.names <- names(dat)}
        names(dat) <- df.names

        ##check and save row number
        row.num[i] <- dim(dat)[1]
        if(row.num[i]!=n) {rm(dat); next}  # each file should have the same number of rows (one per snp)

        ## Sample names for Illumina			
        if(is.element("sample", names(dat))){
            sample.names[[i]] <- unique(dat$sample)
            if(length(sample.names[[i]])>1) {rm(dat);next}	# there should only be one sample per file
            if(sample.names[[i]]!=scan.annotation$scanName[i]) {sample.match[i] <- 0; rm(dat); next}  else {sample.match[i] <- 1}
            ## sample name inside file should match sample.name vector
        }
        ## Sample names for Affy
        if(scan.name.in.file==-1) {
            tmp <- paste(scan.annotation$scanName[i], c("_Call", "_Confidence",".cel"),sep="")
            if(!any(is.element(tmp, tmp.names))) {sample.match[i] <- 0; rm(dat); next} else {sample.match[i] <- 1}
        }	## sample names embedded in file and column names should match

        ##check for duplicate snp names
        if(any(duplicated(dat$snp))) {snp.chk[i] <- 0; rm(dat); next} 

        ##check that all expected snps are present
        if(!setequal(dat$snp,snp.annotation$snpName)) {snp.chk[i] <- 0; rm(dat); next} else snp.chk[i] <- 1

        ##Using the first raw data file to make it this far, put the int.ids in same order as in raw data
        ##	(expecting all to be in this order)
        dat <- dat[match(snp.annotation$snpName, dat$snp),]

        if (allele.coding == "nucleotide") {
            dat <- .mapAlleles(dat, snp.annotation[,c("alleleA", "alleleB")])
        }      
        ##make diploid genotypes if necessary
        if(!is.element("geno", names(dat)) && is.element("a1", names(dat)) && is.element("a2", names(dat))) {
            dat$geno <- paste0(dat$a1, dat$a2)
        }
        ##get character string(s) for missing genotypes - this only works when there is only one code for missing genotype
        ##missg[[i]] <- unique(dat$geno[!is.element(dat$geno,c("AA","AB","BB"))])
        ##if(length(missg[[i]])!=1) { rm(dat); next }
        ##make all missing genotypes blank
        missg[[i]] <- ""
        dat[!is.element(dat$geno,c("AA","AB","BB")),"geno"] <- missg[[i]]
        
        ##load genotypes from ncdf
        geno <- getGenotype(genofile, snp=c(1,n), scan=c(i,1))

        ## convert to AB type
        abtype <- rep(NA, n)
        abtype[is.na(geno)] <- missg[[i]]
        abtype[geno==2] <- "AA"
        abtype[geno==1] <- "AB"
        abtype[geno==0] <- "BB"
        if(length(abtype[is.na(abtype)])!=0) {rm(dat); geno.chk[i] <- 0; next }

        ## compare genotypes
        if(all(abtype==dat$geno)){geno.chk[i] <- 1; rm(geno); rm(abtype)
                              } else {rm(dat); rm(geno); rm(abtype); geno.chk[i] <- 0; next}

        chk[i] <- 1	# made it this far
        if (exists("dat")) rm(dat)
        ## to monitor progress
        if(verbose & i%%10==0) {
            rate <- (Sys.time()-start)/10
            percent <- 100*i/nsx
            message(paste("file", i, "-", format(percent,digits=3), "percent completed - rate =", format(rate,digits=4)))
            start <- Sys.time()
        }


    }	# end of loop

    diagnostics <- list(read.file, row.num, sample.names, sample.match, missg, snp.chk, chk,geno.chk)
    names(diagnostics) <- c("read.file", "row.num", "sample.names", "sample.match", "missg", "snp.chk", "chk",
                            "geno.chk")
    save(diagnostics, file=diagnostics.filename)

    close(genofile)
    return(diagnostics)

}