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Commit 4560b203 authored by Teresa Tavella's avatar Teresa Tavella
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add data and script

parent e777651b
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Paper_figures.Rmd
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---
title: "geing GSEA reactome plot divided by category"
author: ""
pdf_document: default
author: ''
output:
html_document:
html_document: null
df_print: paged
pdf_document: default
word_document: default
pdf_document: default
title: "geing GSEA reactome plot divided by category"
---
......@@ -243,7 +244,7 @@ doHeatmap3 <- function(df, sinfo, num_row_clu = 2, high_genes = NULL, top_annot
width = 10, height = 10,
heatmap_legend_param = list(
title = "Z-score",
at = c(round(min(hm_matrix)),0,round(max(hm_matrix))),
#at = c(round(min(hm_matrix)),0,round(max(hm_matrix))),
legend_direction = "horizontal",
legend_width = unit(4, "cm")),
)
......@@ -286,9 +287,9 @@ mat_gg <- as.data.frame(dimicco$deseq$rlog)[unique(gg), ]
annocat_signif <- annotcat[rownames(mat_gg),]
mat_gg_scaled <- t(scale(t(mat_gg)))
dimicco_hm <- doHeatmap2(df = t(mat_gg_scaled), sinfo = sinfo, high_genes =unique(gg))
rorder <- row_order(dimicco_hm)
mat_gg_scaled_names <- mat_gg_scaled[rorder,]
#dimicco_hm <- doHeatmap2(df = t(mat_gg_scaled), sinfo = sinfo, high_genes =unique(gg))
#rorder <- row_order(dimicco_hm)
#mat_gg_scaled_names <- mat_gg_scaled[rorder,]
annocat_signif <- annocat_signif[,dt$Description]
annocat_signif <- annocat_signif[rownames(mat_gg_scaled ),] # order automatically
......@@ -304,13 +305,13 @@ for (i in dt$Description) {
cn <- dt[dt$Description == i, 'Category']
colors[i] <- my_cols[[cn]]
}
ht3 = Heatmap(as.matrix(annocat_signif), name = " ",show_column_names = TRUE,
show_row_names =FALSE,
border = TRUE,row_names_gp = gpar(fontsize = 4),
column_names_gp = gpar(fontsize = 6, rot = 90),
rect_gp = gpar(col = "black", lwd = 0.5),
col = colors ,na_col = "white",
heatmap_legend_param = list(labels = dt$Category ))#c(rep('', dim(annocat_signif)[2]))) )
# ht3 = Heatmap(as.matrix(annocat_signif), name = " ",show_column_names = TRUE,
# show_row_names =FALSE,
# border = TRUE,row_names_gp = gpar(fontsize = 4),
# column_names_gp = gpar(fontsize = 6, rot = 90),
# rect_gp = gpar(col = "black", lwd = 0.5),
# col = colors ,na_col = "white",
# heatmap_legend_param = list(labels = dt$Category ))#c(rep('', dim(annocat_signif)[2]))) )
## hm of gene in core enrichment and also signif all categories
# svg(filename=paste(plot.dir, paste0("HM_full_categories", "_ON_Old_vs_Young.svg"), sep = "/"),
......@@ -342,17 +343,18 @@ annocat_signif <- annotcat[rownames(mat_gg),]
#annocat_signif <- annocat_signif[,dt$Category]
#annocat_signif <- annocat_signif[rownames(mat_gg_scaled ),] # order automatically
table(rownames(annocat_signif ) == rownames(mat_gg_scaled))
my_cols <- c(hue_pal()(length(levels(dt$Category))))
names(my_cols) <- levels(dt$Category)
ht3 = Heatmap(as.matrix(annocat_signif), name = " ",show_column_names = TRUE,
show_row_names =FALSE,
border = TRUE,row_names_gp = gpar(fontsize = 12),
column_names_gp = gpar(fontsize = 12, rot = 90),
rect_gp = gpar(col = "black", lwd = 0.5),
col = my_cols ,na_col = "white",
heatmap_legend_param = list(labels = levels(dt$Category) ))#c(rep('', dim(annocat_signif)[2]))) )
# ht3 = Heatmap(as.matrix(annocat_signif), name = " ",show_column_names = TRUE,
# show_row_names =FALSE,
# border = TRUE,row_names_gp = gpar(fontsize = 12),
# column_names_gp = gpar(fontsize = 12, rot = 90),
# rect_gp = gpar(col = "black", lwd = 0.5),
# col = my_cols ,na_col = "white",
# heatmap_legend_param = list(labels = levels(dt$Category) ))#c(rep('', dim(annocat_signif)[2]))) )
# svg(filename=paste(plot.dir, paste0("HM_reduced_categories", "_ON_Old_vs_Young.svg"), sep = "/"),
# width=12,
......@@ -394,52 +396,52 @@ dev.off()
##### HM of genes in the core enrichment and also signif single HM
```{r echo=FALSE,echo=FALSE, warning=FALSE,message=FALSE}
#######################################################
for (y in unique(dt$Category)) { ## for each macro category
gg <- c()
for (n in names(real_sig)) {
if (n %in% dt[dt$Category == y,'Description']){
print(n)
#gg <- rownames(real_sig[[n]])
gg <- append(gg,rownames(real_sig[[n]]))
}
}
gx <- unique(gg)
mat_gg <- as.data.frame(dimicco$deseq$rlog)[gx, ]
mat_gg_scaled <- t(scale(t(mat_gg)))
dimicco_hm <- doHeatmap2(df = mat_gg_scaled, sinfo = sinfo)
str(sinfo)
n <- gsub(' ','_',gsub('/','_',n))
# svg(filename=paste(plot.dir, paste0("HM_", y, "_ON_Old_vs_Young.svg"), sep = "/"),
# width=6,
# height=6,
# pointsize=12)
# draw(dimicco_hm)
# dev.off()
#
if (length(gx) > 39) {
png(filename=paste(plot.dir, paste0("HM_", y, "_ON_Old_vs_Young.png"), sep = "/"),
units = "in", width = 8, height = 25, res = 300)
draw(dimicco_hm, merge_legend = TRUE,heatmap_legend_side = 'top',column_title =y)
dev.off()
} else if (length(gx) > 22) {
png(filename=paste(plot.dir, paste0("HM_", y, "_ON_Old_vs_Young.png"), sep = "/"),
units = "in", width = 5, height = 8, res = 300)
draw(dimicco_hm, merge_legend = TRUE,heatmap_legend_side = 'top',column_title =y)
dev.off()
} else if (length(gx) > 10) {
png(filename=paste(plot.dir, paste0("HM_", y, "_ON_Old_vs_Young.png"), sep = "/"),
units = "in", width = 5, height = 6, res = 300)
draw(dimicco_hm, merge_legend = TRUE,heatmap_legend_side = 'top',column_title =y)
dev.off()
} else {
png(filename=paste(plot.dir, paste0("HM_", y, "_ON_Old_vs_Young.png"), sep = "/"),
units = "in", width = 4, height = 4, res = 300)
draw(dimicco_hm, merge_legend = TRUE,heatmap_legend_side = 'top',column_title =y)
dev.off()
}
}
#
# for (y in unique(dt$Category)) { ## for each macro category
# gg <- c()
# for (n in names(real_sig)) {
# if (n %in% dt[dt$Category == y,'Description']){
# print(n)
# #gg <- rownames(real_sig[[n]])
# gg <- append(gg,rownames(real_sig[[n]]))
# }
# }
# gx <- unique(gg)
# mat_gg <- as.data.frame(dimicco$deseq$rlog)[gx, ]
# mat_gg_scaled <- t(scale(t(mat_gg)))
# dimicco_hm <- doHeatmap2(df = mat_gg_scaled, sinfo = sinfo)
#
# str(sinfo)
# n <- gsub(' ','_',gsub('/','_',n))
# # svg(filename=paste(plot.dir, paste0("HM_", y, "_ON_Old_vs_Young.svg"), sep = "/"),
# # width=6,
# # height=6,
# # pointsize=12)
# # draw(dimicco_hm)
# # dev.off()
# #
# if (length(gx) > 39) {
# png(filename=paste(plot.dir, paste0("HM_", y, "_ON_Old_vs_Young.png"), sep = "/"),
# units = "in", width = 8, height = 25, res = 300)
# draw(dimicco_hm, merge_legend = TRUE,heatmap_legend_side = 'top',column_title =y)
# dev.off()
# } else if (length(gx) > 22) {
# png(filename=paste(plot.dir, paste0("HM_", y, "_ON_Old_vs_Young.png"), sep = "/"),
# units = "in", width = 5, height = 8, res = 300)
# draw(dimicco_hm, merge_legend = TRUE,heatmap_legend_side = 'top',column_title =y)
# dev.off()
# } else if (length(gx) > 10) {
# png(filename=paste(plot.dir, paste0("HM_", y, "_ON_Old_vs_Young.png"), sep = "/"),
# units = "in", width = 5, height = 6, res = 300)
# draw(dimicco_hm, merge_legend = TRUE,heatmap_legend_side = 'top',column_title =y)
# dev.off()
# } else {
# png(filename=paste(plot.dir, paste0("HM_", y, "_ON_Old_vs_Young.png"), sep = "/"),
# units = "in", width = 4, height = 4, res = 300)
# draw(dimicco_hm, merge_legend = TRUE,heatmap_legend_side = 'top',column_title =y)
# dev.off()
# }
# }
```
data/HM_reduced_categories_reverse_ON_Old_vs_Young_v1.svg
View file @ 4560b203
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