Nothing
dmSQTL_CRadjustmentManyGroups_gene <- function(g, counts, genotypes,
prec, fit, verbose){
if(verbose >= 2) message(" Gene:", g)
y <- counts[[g]]
x <- genotypes[[g]]
a <- numeric(nrow(x))
for(i in 1:nrow(x)){
# i = 2
NAs <- is.na(x[i, ]) | is.na(y[1, ])
yy <- y[, !NAs, drop = FALSE]
xx <- x[i, !NAs]
ff <- fit[[g]][[i]][, !NAs, drop = FALSE]
groups <- factor(xx)
ngroups <- nlevels(groups)
lgroups <- levels(groups)
igroups <- lapply(lgroups, function(gr){which(groups == gr)})
names(igroups) <- lgroups
# Get the column number of a first occurance of a group level
figroups <- unlist(lapply(igroups, function(x){x[1]}))
a[i] <- dm_CRadjustmentManyGroups(y = yy,
ngroups = ngroups, lgroups = lgroups, igroups = igroups,
prec = prec[[g]][i], prop = ff[, figroups, drop = FALSE])
}
# a vector of length #snps for gene g
return(a)
}
#' @importFrom stats model.matrix
dmSQTL_CRadjustmentRegression_gene <- function(g, counts, genotypes,
group_formula = ~ group, prec, fit, verbose){
if(verbose >= 2) message(" Gene:", g)
y <- counts[[g]]
x <- genotypes[[g]]
a <- numeric(nrow(x))
for(i in 1:nrow(x)){
# i = 2
NAs <- is.na(x[i, ]) | is.na(y[1, ])
yy <- y[, !NAs, drop = FALSE]
xx <- x[i, !NAs]
ff <- fit[[g]][[i]][, !NAs, drop = FALSE]
design <- model.matrix(group_formula, data = data.frame(group = xx))
a[i] <- dm_CRadjustmentRegression(y = yy, x = design,
prec = prec[[g]][i], prop = ff)
}
# a vector of length #snps for gene g
return(a)
}
dmSQTL_CRadjustment <- function(counts, fit, genotypes,
group_formula = ~ group, precision, one_way = TRUE,
verbose = FALSE, BPPARAM = BiocParallel::SerialParam()){
time_start <- Sys.time()
if(verbose) message("* Calculating Cox-Reid adjustment.. \n")
inds <- 1:length(counts)
# Prepare precision
if(class(precision) == "numeric"){
prec <- relist(rep(precision, nrow(genotypes)), genotypes@partitioning)
} else {
prec <- precision
}
if(one_way){
adj <- BiocParallel::bplapply(inds,
dmSQTL_CRadjustmentManyGroups_gene, counts = counts,
genotypes = genotypes, prec = prec, fit = fit,
verbose = verbose, BPPARAM = BPPARAM)
names(adj) <- names(counts)
}else{
adj <- BiocParallel::bplapply(inds,
dmSQTL_CRadjustmentRegression_gene, counts = counts,
genotypes = genotypes, group_formula = ~ group, prec = prec, fit = fit,
verbose = verbose, BPPARAM = BPPARAM)
names(adj) <- names(counts)
}
time_end <- Sys.time()
if(verbose >= 2) message("\n")
if(verbose) message("Took ", round(time_end - time_start, 4), " seconds.\n")
# adj is a list of length G
return(adj)
}
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