--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/scripts/cluster.R	Thu Nov 22 04:45:41 2018 -0500
@@ -0,0 +1,156 @@
+#!/usr/bin/env R
+VERSION = "0.2"
+
+args = commandArgs(trailingOnly = T)
+
+if (length(args) != 1){
+     message(paste("VERSION:", VERSION))
+     stop("Please provide the config file")
+}
+
+suppressWarnings(suppressPackageStartupMessages(require(RaceID)))
+suppressWarnings(suppressPackageStartupMessages(require(scran)))
+source(args[1])
+
+
+do.filter <- function(sc){
+    if (!is.null(filt.lbatch.regexes)){
+        lar <- filt.lbatch.regexes
+        nn <- colnames(sc@expdata)
+        filt$LBatch <- lapply(1:length(lar), function(m){ return( nn[grep(lar[[m]], nn)] ) })
+    }
+
+    sc <- do.call(filterdata, c(sc, filt))
+
+    ## Get histogram metrics for library size and number of features
+    raw.lib <- log(colSums(as.matrix(sc@expdata)))
+    raw.feat <- log(rowSums(as.matrix(sc@expdata)))
+    filt.lib <- log(colSums(getfdata(sc)))
+    filt.feat <- log(rowSums(getfdata(sc)))
+
+    br <- 50
+    ## Determine limits on plots based on the unfiltered data
+    ## (doesn't work, R rejects limits and norm data is too different to compare to exp data
+    ##  so let them keep their own ranges)
+
+    ## betterrange <- function(floatval){
+    ##     return(10 * (floor(floatval / 10) + 1))
+    ## }
+
+    ## tmp.lib <- hist(raw.lib, breaks=br, plot=F)
+    ## tmp.feat <- hist(raw.feat, breaks=br, plot=F)
+
+    ## lib.y_lim <- c(0,betterrange(max(tmp.lib$counts)))
+    ## lib.x_lim <- c(0,betterrange(max(tmp.lib$breaks)))
+
+    ## feat.y_lim <- c(0,betterrange(max(tmp.feat$counts)))
+    ## feat.x_lim <- c(0,betterrange(max(tmp.feat$breaks)))
+
+    par(mfrow=c(2,2))
+    print(hist(raw.lib, breaks=br, main="ExpData Log(LibSize)")) # , xlim=lib.x_lim, ylim=lib.y_lim)
+    print(hist(raw.feat, breaks=br, main="ExpData Log(NumFeat)")) #, xlim=feat.x_lim, ylim=feat.y_lim)
+    print(hist(filt.lib, breaks=br, main="FiltData Log(LibSize)")) # , xlim=lib.x_lim, ylim=lib.y_lim)
+    print(hist(filt.feat, breaks=br, main="FiltData Log(NumFeat)")) # , xlim=feat.x_lim, ylim=feat.y_lim)
+
+    if (filt.use.ccorrect){
+        par(mfrow=c(2,2))
+        sc <- do.call(CCcorrect, c(sc, filt.ccc))
+        print(plotdimsat(sc, change=T))
+        print(plotdimsat(sc, change=F))
+    }
+    return(sc)
+}
+
+do.cluster <- function(sc){
+    sc <- do.call(compdist, c(sc, clust.compdist))
+    sc <- do.call(clustexp, c(sc, clust.clustexp))
+    if (clust.clustexp$sat){
+        print(plotsaturation(sc, disp=F))
+        print(plotsaturation(sc, disp=T))
+    }
+    print(plotjaccard(sc))
+    return(sc)
+}
+
+do.outlier <- function(sc){
+    sc <- do.call(findoutliers, c(sc, outlier.findoutliers))
+    if (outlier.use.randomforest){
+        sc <- do.call(rfcorrect, c(sc, outlier.rfcorrect))
+    }
+    print(plotbackground(sc))
+    print(plotsensitivity(sc))
+    print(plotoutlierprobs(sc))
+    ## Heatmaps
+    test1 <- list()
+    test1$side = 3
+    test1$line = 0  #1 #3
+
+    x <- clustheatmap(sc, final=FALSE)
+    print(do.call(mtext, c(paste("(Initial)"), test1)))  ## spacing is a hack
+    x <- clustheatmap(sc, final=TRUE)
+    print(do.call(mtext, c(paste("(Final)"), test1)))  ## spacing is a hack
+    return(sc)
+}
+
+do.clustmap <- function(sc){
+    sc <- do.call(comptsne, c(sc, cluster.comptsne))
+    sc <- do.call(compfr, c(sc, cluster.compfr))
+    return(sc)
+}
+
+
+mkgenelist <- function(sc){
+    ## Layout
+    test <- list()
+    test$side = 3
+    test$line = 0  #1 #3
+    test$cex = 0.8
+
+    df <- c()
+    options(cex = 1)
+    lapply(unique(sc@cpart), function(n){
+        dg <- clustdiffgenes(sc, cl=n, pvalue=genelist.pvalue)
+
+        dg.goi <- dg[dg$fc > genelist.foldchange,]
+        dg.goi.table <- head(dg.goi, genelist.tablelim)
+        df <<- rbind(df, cbind(n, dg.goi.table))
+
+        goi <- head(rownames(dg.goi.table), genelist.plotlim)
+        print(plotmarkergenes(sc, goi))
+        print(do.call(mtext, c(paste("                               Cluster ",n), test)))  ## spacing is a hack
+        test$line=-1
+        print(do.call(mtext, c(paste("                               Sig. Genes"), test)))  ## spacing is a hack
+        test$line=-2
+        print(do.call(mtext, c(paste("                               (fc > ", genelist.foldchange,")"), test)))  ## spacing is a hack
+
+    })
+    write.table(df, file=out.genelist, sep="\t", quote=F)
+}
+
+pdf(out.pdf)
+
+if (use.filtnormconf){
+    sc <- do.filter(sc)
+    message(paste(" - Source:: genes:",nrow(sc@expdata),", cells:",ncol(sc@expdata)))
+    message(paste(" - Filter:: genes:",nrow(sc@ndata),", cells:",ncol(sc@ndata)))
+    message(paste("         :: ",
+                  sprintf("%.1f", 100 * nrow(sc@ndata)/nrow(sc@expdata)), "% of genes remain,",
+                  sprintf("%.1f", 100 * ncol(sc@ndata)/ncol(sc@expdata)), "% of cells remain"))
+}
+
+if (use.cluster){
+    par(mfrow=c(2,2))
+    sc <- do.cluster(sc)
+
+    par(mfrow=c(2,2))
+    sc <- do.outlier(sc)
+
+    par(mfrow=c(2,2), mar=c(1,1,6,1))
+    sc <- do.clustmap(sc)
+
+    mkgenelist(sc)
+}
+
+dev.off()
+
+saveRDS(sc, out.rdat)