--- a
+++ b/Fig6B_S6F_CGA_tSNEplot_hemap.R
@@ -0,0 +1,88 @@
+GIT_HOME="/research/users/ppolonen/git_home/ImmunogenomicLandscape-BloodCancers/"
+source(file.path(GIT_HOME, "common_scripts/visualisation/plotting_functions.R"))
+source(file.path(GIT_HOME, "common_scripts/statistics/functions_statistics.R"))
+source(file.path(GIT_HOME, "common_scripts/pathway_analysis/functions.GSEA.R"))
+
+setwd("/research/groups/sysgen/PROJECTS/HEMAP_IMMUNOLOGY/petri_work/HEMAP_IMMUNOLOGY/Published_data_figures")
+t.df = read.delim("t.antigen_df.txt", stringsAsFactors=F, header=T)
+
+annot = get(load("Hemap_immunology_Annotations.Rdata"))
+
+# gexp data
+data=t(get(load("data9544_with_gene_symbols.RData")))
+data=data[,colnames(data)%in%annot$GSM.identifier..sample.]
+
+t.df=t.df[order(t.df[,3]),]
+t.df=t.df[t.df$name%in%"Cancer_Myeloma",]
+# rank patients by number of testis antigens expressed
+# profiles
+profile=get(load("/research/groups/sysgen/PROJECTS/HEMAP/HEMAP/dat2figs/revision_2018/petri/mixtureM_profile.Rdata"))
+profile[profile==-1] = 0
+profile2=profile[,colnames(profile)%in%annot$GSM.identifier..sample.]
+
+# take only high expressed into account
+profile2[data.matrix(data)<5]=0
+
+expressed_testis_num=colSums(profile2[rownames(profile2)%in%unique(t.df$gene),])
+feat_class=expressed_testis_num
+feat_class[expressed_testis_num==0]="0_Antigens"
+feat_class[expressed_testis_num>=1&expressed_testis_num<=4]="1to4_Antigens"
+feat_class[expressed_testis_num>=5&expressed_testis_num<=6]="5to6_Antigens"
+feat_class[expressed_testis_num>=7]="over7_Antigens"
+
+# plot CGA to hemap:
+
+colorv=rep("grey75", length(annot$y))
+
+colorf=colorRamp2(breaks = c(0, 2, 4, 6, 7),colors = c("grey75", "#f4acac", "#f77777", "#e23030", "#800000"))
+
+Plot_color_vector=function(X, color, NAME=NULL, SIZE=0.8, TITLE="tSNE plot", PATH_OUTPUT=getwd(), peaks=NULL) {
+  
+  # if cluster centers are not defined as inputs, do not plot them.
+  CLUSTER_CENTRE=ifelse(is.null(peaks), F, T)
+  
+  # Color vector
+  datCol=color
+  
+  # Prepare input matrix for plotting.
+  dat2show <- cbind(X$x, X$y)
+  df=as.data.frame(dat2show)
+  colnames(df) = c("X1","X2")
+  
+  # If for some reason we use a color vector which includes blanks,
+  # create a color vector without them to be plotted at the front.
+  # (Increases visibility of the "important" colored samples.)
+  front=!datCol==""
+  
+  # Call actual plotting function.
+  p=drawFig(df, CLUSTER_CENTRE, datCol, front, TITLE, SIZE, peaks)
+  
+  if(!is.null(NAME)){
+    # Write out print quality figure as PDF.
+    ggsave(paste0(PATH_OUTPUT, NAME, "_singlepage.pdf"), p, width = 210, height = 210, units = "mm", dpi=150)
+  }
+  return(p)
+}
+
+pdf("FigS6B_TSNE_CGA_hemap.pdf", width = 6.5, height = 6)
+Plot_color_vector(X = data.frame("x"=annot$x, "y"=annot$y), color = colorf(expressed_testis_num), NAME = "FigS6B_TSNE_CGA_hemap.pdf")
+dev.off()
+
+# Only hemap MM
+load("Hemap_MM_subtypes.Rdata")
+
+# plot CGA to hemap:
+expressed_testis_num=colSums(profile2[rownames(profile2)%in%unique(t.df$gene),])
+feat_class=expressed_testis_num
+feat_class[expressed_testis_num==0]="0_Antigens"
+feat_class[expressed_testis_num>=1&expressed_testis_num<=2]="1to2_Antigens"
+feat_class[expressed_testis_num>=3&expressed_testis_num<=4]="3to4_Antigens"
+feat_class[expressed_testis_num>=5&expressed_testis_num<=6]="5to6_Antigens"
+feat_class[expressed_testis_num>=7]="over7_Antigens"
+
+
+colorf=colorRamp2(breaks = c(0, 2, 4, 6, 7),colors = c("grey75", "#f4acac", "#f77777", "#e23030", "#800000"))
+
+pdf("FigS6F_TSNE_CGA_hemap_MM_subtypes.pdf", width = 6.5, height = 6)
+Plot_color_vector(X = data.frame("x"=coordinates.subtype$x, "y"=coordinates.subtype$y), color = colorf(expressed_testis_num[match(coordinates.subtype$ID, names(expressed_testis_num))]), NAME = "TSNE_CGA_hemap.pdf", SIZE = 4)
+dev.off()
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