打分模型 | 基因表达

#
get.bg.lists <- function(goi, N, expr.bin) {
  res <- list()
  goi.bin.tab <- table(expr.bin[goi])
  for (i in 1:N) {
    res[[i]] <- unlist(lapply(names(goi.bin.tab), function(b) {
      sel <- which(expr.bin == as.numeric(b) & !(names(expr.bin) %in% goi))
      sample(names(expr.bin)[sel], goi.bin.tab[b])
    }))
  }
  return(res)
}

#
enr.score <- function(expr, goi, bg.lst) {
  goi.mean <- apply(expr[goi, ], 2, mean)
  bg.mean <- sapply(1:length(bg.lst), function(i) apply(expr[bg.lst[[i]], ], 2, mean))
  return((goi.mean - apply(bg.mean, 1, mean)) / apply(bg.mean, 1, sd))
}

#
get.cc.score <- function(cm, N=100, seed=42) {
  set.seed(seed)
  cat(‘get.cc.score, ‘)
  cat(‘number of random background gene sets set to‘, N, ‘\n‘)
  
  min.cells <- 5
  
  cells.mols <- apply(cm, 2, sum)
  gene.cells <- apply(cm>0, 1, sum)
  cm <- cm[gene.cells >= min.cells, ]
  
  gene.mean <- apply(cm, 1, mean)
  
  breaks <- unique(quantile(log10(gene.mean), probs = seq(0,1, length.out = 50)))
  gene.bin <- cut(log10(gene.mean), breaks = breaks, labels = FALSE)
  names(gene.bin) <- rownames(cm)
  gene.bin[is.na(gene.bin)] <- 0
  
  regev.s.genes <- read.table(file=‘./annotation/s_genes.txt‘, header=FALSE, stringsAsFactors=FALSE)$V1
  regev.g2m.genes <- read.table(file=‘./annotation/g2m_genes.txt‘, header=FALSE, stringsAsFactors=FALSE)$V1
  
  goi.lst <- list(‘S‘=rownames(cm)[!is.na(match(toupper(rownames(cm)), regev.s.genes))],
                  ‘G2M‘=rownames(cm)[!is.na(match(toupper(rownames(cm)), regev.g2m.genes))])
  
  n <- min(40, min(sapply(goi.lst, length)))
  goi.lst <- lapply(goi.lst, function(x) x[order(gene.mean[x], decreasing = TRUE)[1:n]])
  
  bg.lst <- list(‘S‘=get.bg.lists(goi.lst[[‘S‘]], N, gene.bin),
                 ‘G2M‘=get.bg.lists(goi.lst[[‘G2M‘]], N, gene.bin))
  
  all.genes <- sort(unique(c(unlist(goi.lst, use.names=FALSE), unlist(bg.lst, use.names=FALSE))))
  
  expr <- log10(cm[all.genes, ]+1)
  
  s.score <- enr.score(expr, goi.lst[[‘S‘]], bg.lst[[‘S‘]])
  g2m.score <- enr.score(expr, goi.lst[[‘G2M‘]], bg.lst[[‘G2M‘]])
  
  phase <- as.numeric(g2m.score > 2 & s.score <= 2)
  phase[g2m.score <= 2 & s.score > 2] <- -1
  
  return(data.frame(score=s.score-g2m.score, s.score, g2m.score, phase))
}