R/old/map.loc.lme.R

In behuang/dlmap: Detection Localization Mapping for QTL

`map.loc.lme` <-
function(input, s.chr, chrSet, prevLoc=NULL)
{
  dfMerged <- input$dfMerged
  fixed <- input$envModel$fixed
  n.chr <- length(input$map)
  map <- input$mapp[[s.chr]]
  mrk <- grep(paste("C", s.chr, "M", sep=""), names(dfMerged))
  chr <- sort(c(mrk, grep(paste("C", s.chr, "P", sep=""), names(dfMerged))))
  type <- attr(input, "type")

  results <- list()
  formula <- list()
  chrRE <- vector()

  if (type=="f2") mrk <- mrk[seq(1, length(mrk), 2)]

  wald <- rep(0, length(map))

  f.pos <- vector()
  f.mrk <- vector()
  if (length(prevLoc)>0) {
    f.pos <- prevLoc$pos
    f.mrk <- prevLoc$mrk
 
    if (type=="f2") {
      	f.pos <- paste(unique(substr(f.pos, 1, nchar(f.pos)-1)), "D", sep="")
      	f.mrk <- unique(substr(f.mrk, 1, nchar(f.mrk)-1))
    }
  }

  # Set up random effects for markers on each chromosome	
  for (kk in 1:n.chr)
  chrRE[kk] <- paste("pdIdent(~", paste(setdiff(names(dfMerged)[grep(paste("C", kk, "M", sep=""), names(dfMerged))], prevLoc$mrk), collapse="+"), "-1)", sep="")

  int <- vector()
  if (length(f.pos)>0) {
    fmrk <- sapply(match(f.pos, names(dfMerged)), function(x) {
	if (x==min(mrk)) return(c(min(mrk), min(mrk[mrk>x]))) else if (x==max(mrk)) return(c(max(mrk[mrk<x]), max(mrk))) else return(c(max(mrk[mrk<x]), min(mrk[mrk>x])))})

  # because we want to exclude both additive and dominant effects
  if (type=="f2") fmrk[2,] <- fmrk[2,]+1

  int <- eval(parse(text=paste("c(", paste(apply(fmrk, 2, function(x) return(paste(x[1], ":", x[2], sep=""))), collapse=","), ")", sep="")))
  }

  # Loop over chrPos on the selected chromosome
  for (jj in 1:length(map))
  {
	if (type=="f2") pos <- c(2*jj-1, 2*jj) else pos <- jj
	
	if (all(!(chr[pos] %in% int)))	
	{
	  if (length(chrSet)>2)
	     formula$random <- paste("pdBlocked(list(", paste(chrRE[setdiff(chrSet,s.chr)], collapse=","), "))", sep="")

	  if (length(chrSet)==2)
	     formula$random <- chrRE[setdiff(chrSet, s.chr)]

	  formula$fixed <- paste(as.character(fixed)[2], "~", as.character(fixed)[3], sep="")

	# If there are markers already mapped on other chromosomes, add in as fixed effects 
	  if (length(f.pos) >0)
	     formula$fixed <- paste(formula$fixed, "+",paste(prevLoc$pos, collapse="+"), sep="")

	effectnames <- names(dfMerged)[chr[pos]]
	
	formula$fixed <- paste(formula$fixed, "+", paste(effectnames, collapse="+"), sep="") 

	formula$fixgrp <- paste(formula$fixed, "| grp1", sep="")
	formula$fixgrp <- as.formula(formula$fixgrp)
	formula$fixed <- as.formula(formula$fixed)

	gd <- groupedData(formula$fixgrp, data=dfMerged)

	# Fit model - different forms depending on relevant terms
	if (length(chrSet)>1)
	model <- lme(fixed=formula$fixed, random=eval(parse(text=formula$random)), data=gd, control=lmeControl(maxIter=input$maxit), na.action=na.omit)

	if (length(chrSet)==1)
	model <- lme(fixed=formula$fixed, random=~1|grp1, data=gd, control=lmeControl(maxIter=input$maxit), na.action=na.omit)

	# Get output - Wald statistic for position fixed effect
	############## need to put in a check for f2 here to get proper Wald####
	wald[jj] <- anova(model, Terms=effectnames)[1,3]
	} # end of check for distinct intervals
  }

  results$wald <- wald

  return(results)
}