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# summary for maker maps
summaryGenMap <- function(map, cores=1){
multiLapply <- function(x,y,...,cores=cores){
if(.Platform$OS.type == "windows" & cores>1){
cl <- makeCluster(min(cores, detectCores()))
registerDoParallel(cl)
parLapply(cl,x,y,...)
stopCluster(cl)
} else {
mclapply(x,y,...,mc.cores=cores)
}
}
# information from arguments
if(class(map)=="gpData") map <- map$map
if(is.null(map)) stop("No map available")
chr <- map$chr
pos <- map$pos
# extract information
# number of markers
len <- tapply(pos,chr,length)
rge <- tapply(pos,chr,max,na.rm=TRUE)-tapply(pos,chr,min,na.rm=TRUE)
# differences of markers on each chr
diffs <- tapply(pos[!is.na(pos)],chr[!is.na(pos)],diff,na.rm=TRUE)
avDist <- as.numeric(multiLapply(diffs,mean,na.rm=TRUE, cores=cores))
maxDist <- as.numeric(multiLapply(diffs,max,na.rm=TRUE, cores=cores))
minDist <- as.numeric(multiLapply(diffs,min,na.rm=TRUE, cores=cores))
# return data.frame
ret <- data.frame(noM = len, length=rge, avDist = avDist, maxDist = maxDist, minDist = minDist,row.names=names(len))
# keep same order as original map
ret <- ret[order(order(unique(chr))),]
# sum over all chr
all <- data.frame(noM = sum(ret$noM,na.rm=TRUE),length= sum(ret$length,na.rm=TRUE),avDist=weighted.mean(ret$avDist,ret$noM,na.rm=TRUE),maxDist=max(ret$maxDist,na.rm=TRUE),minDist=min(ret$minDist,na.rm=TRUE))
rownames(all) <- paste(rownames(ret)[1],"-",rownames(ret)[nrow(ret)])
ret <- rbind(ret,all)
return(ret)
}
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