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minor changes in color scale
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also changed the functions used to retrieve data to remove the requirement of a subfolder in the working directory.
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@wfma
wfma committed Jan 1, 2019
1 parent df9f5af commit fb376db
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Showing 2 changed files with 34 additions and 136 deletions.
9 changes: 4 additions & 5 deletions [FINAL] NADPH-GenePanels-HEATMAP.R
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Original file line number Diff line number Diff line change
Expand Up @@ -465,12 +465,11 @@ dl.RNA.select <- function(y) {
# CNV_SNP = T, # copy number alterantion in germline cells
# Methylation = T, # methylation provided by array platform
# RPPA = T, # reverse phase protein array expression
RNAseq2_Gene_Norm = TRUE,
RNASeq2GeneNorm = T,
RNAseq2Norm = "normalized_count",
# normalized count
fileSizeLimit = 99999,
# getUUIDs = T,
destdir = "FireHose Data",
forceDownload = F
forceDownload = T
)
edit <- gather(rownames_to_column(as.data.frame(getData(set, type = "RNASeq2GeneNorm")), var = "Gene.Symbol"),
key = "Patient.ID", value = "mRNA.Value", -Gene.Symbol) # extract RNAseq, transform row name as a colmn, then transform into long form
Expand Down Expand Up @@ -757,7 +756,7 @@ calc.rho.unclustered.no_p53 <-
pretty.order.cols = TRUE,
left.label.text.alignment = "right",
bottom.label.text.alignment = "right",
heat.pal = c("turquoise", "white", "violetred1"),
heat.pal = c("deepskyblue3", "white", "red2"),
heat.lim = c(-1,1),
legend.breaks = c(-0.8,0,0.8)
)
Expand Down
161 changes: 30 additions & 131 deletions [FINAL] NOX4-EMT-HEATMAP_UnsupervisedClustered.R
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Original file line number Diff line number Diff line change
Expand Up @@ -11,8 +11,9 @@ library(tibble)
library(ggforce)
library(superheat)
# custom install from github,
# install.packages("devtools")
# devtools::install_github("rlbarter/superheat")
# source("https://install-github.me/r-lib/callr") # install callr dependency for devtools
# install.packages("devtools") # install devtools
# devtools::install_github("rlbarter/superheat") # use devtools to install superheat
library(dplyr)

### Set Working Directory PLEASE ADJUST TO YOUR COMPUTER ----
Expand Down Expand Up @@ -462,12 +463,11 @@ dl.RNA.select <- function(y) {
# CNV_SNP = T, # copy number alterantion in germline cells
# Methylation = T, # methylation provided by array platform
# RPPA = T, # reverse phase protein array expression
RNAseq2_Gene_Norm = TRUE,
RNASeq2GeneNorm = T,
RNAseq2Norm = "normalized_count",
# normalized count
fileSizeLimit = 99999,
# getUUIDs = T,
destdir = "FireHose Data",
forceDownload = F
forceDownload = T
)
edit <- gather(rownames_to_column(as.data.frame(getData(set, type = "RNASeq2GeneNorm")), var = "Gene.Symbol"),
key = "Patient.ID", value = "mRNA.Value", -Gene.Symbol) # extract RNAseq, transform row name as a colmn, then transform into long form
Expand Down Expand Up @@ -719,7 +719,7 @@ calc.rho.unclustered.no_p53 <-
pretty.order.cols = TRUE,
left.label.text.alignment = "right",
bottom.label.text.alignment = "right",
heat.pal = c("turquoise", "white", "violetred1"),
heat.pal = c("deepskyblue3", "white", "red2"),
heat.lim = c(-0.8,0.8))

dev.off()
Expand Down Expand Up @@ -762,7 +762,7 @@ head(Pan.final)
#### NADPHoxidase correlations to genepanels faceted by p53 ----


Make.heatmap.p53 <- function(NOX.master = "NOX4", gene_list_master = EMT.SAbiosci.genes, dpi = 600, wid = 9, hei = 4) {
Make.heatmap.p53 <- function(NOX.master = "NOX4", BLsize = 1, gene_list_master = EMT.SAbiosci.genes, dpi = 600, wid = 9, hei = 4) {

filter.nox <- function(NOX = NOX.master, mutation, gene_list = gene_list_master) {
# outputs the rho of the specificed NOX to the specified genes in the specific p53 mutant group
Expand Down Expand Up @@ -847,7 +847,7 @@ Make.heatmap.p53 <- function(NOX.master = "NOX4", gene_list_master = EMT.SAbiosc
superheat(
combined.rho.final,
bottom.label.text.angle = 90,
bottom.label.text.size = 3,
bottom.label.text.size = 4,
scale = F,
grid.hline.col = "white",
grid.vline.col = "white",
Expand All @@ -857,7 +857,8 @@ Make.heatmap.p53 <- function(NOX.master = "NOX4", gene_list_master = EMT.SAbiosc
pretty.order.cols = T,
left.label.text.alignment = "right",
bottom.label.text.alignment = "right",
heat.pal = c("turquoise", "white", "violetred1"),
bottom.label.size = BLsize,
heat.pal = c("deepskyblue3", "white", "red2"),
heat.lim = c(-1,1),
legend.breaks = c(-0.8,0,0.8))

Expand All @@ -870,7 +871,7 @@ Make.heatmap.p53 <- function(NOX.master = "NOX4", gene_list_master = EMT.SAbiosc
superheat(
combined.rho.final,
bottom.label.text.angle = 90,
bottom.label.text.size = 3,
bottom.label.text.size = 4,
scale = F,
grid.hline.col = "white",
grid.vline.col = "white",
Expand All @@ -880,132 +881,22 @@ Make.heatmap.p53 <- function(NOX.master = "NOX4", gene_list_master = EMT.SAbiosc
row.dendrogram = T,
left.label.text.alignment = "right",
bottom.label.text.alignment = "right",
heat.pal = c("turquoise", "white", "violetred1"),
heat.lim = c(-1,1),
legend.breaks = c(-0.8,0,0.8))


dev.off()
}
Make.heatmap.p53.n <- function(NOX.master = "NOX4", gene_list_master = EMT.SAbiosci.genes, dpi = 600, wid = 9, hei = 4) {
# this function will attach a yplot with n to the heatmap
filter.nox <- function(NOX = NOX.master, mutation, gene_list = gene_list_master) {
# outputs the rho of the specificed NOX to the specified genes in the specific p53 mutant group
# I chosed not to use piping operator on purpose to examine each df created
df.0 <-
Pan.final[Pan.final$P53.Mutation %in% mutation,] # isolate an individual mutant
df.1 <- select(df.0, -Case.Study) # removes case study column
df.2 <- unique(df.1, nmax = 2)
df.3 <-
spread(data = df.2,
key = Gene.Symbol,
value = mRNA.Value) # change to wide format to make matrix
rownames(df.3) <- df.3$Patient.ID
df.4 <- select(df.3, -Patient.ID, -P53.Mutation)
df.cor <-
cor(df.4, method = "spearman", use = "pairwise.complete.obs")
df.5 <- t(as.matrix(df.cor[NOX, ]))
rownames(df.5) <- mutation

# so now df.5 is the defined row with rho values

df.6 <- df.5[, gene_list]
df.6
}

R175H <- filter.nox(mutation = "R175H")
R248Q <- filter.nox(mutation = "R248Q")
R273H <- filter.nox(mutation = "R273H")
R273C <- filter.nox(mutation = "R273C")
R248W <- filter.nox(mutation = "R248W")
Y220C <- filter.nox(mutation = "Y220C")
R249S <- filter.nox(mutation = "R249S")
G245D <- filter.nox(mutation = "G245D")
R273C <- filter.nox(mutation = "R273C")
R248Q <- filter.nox(mutation = "R248Q")
H179R <- filter.nox(mutation = "H179R")
R282W <- filter.nox(mutation = "R282W")
V157F <- filter.nox(mutation = "V157F")
H193R <- filter.nox(mutation = "H193R")
R158L <- filter.nox(mutation = "R158L")
R273L <- filter.nox(mutation = "R273L")
R158L <- filter.nox(mutation = "R158L")
H179R <- filter.nox(mutation = "H179R")
G245S <- filter.nox(mutation = "G245S")
WT <- filter.nox(mutation = "WT")

all_grouping <- rbind(
R175H,
R248Q,
R273H,
R273C,
R248W,
Y220C,
R249S,
G245D,
R273C,
R248Q,
H179R,
R282W,
V157F,
H193R,
R158L,
R273L,
# G248S, # very few of these
R158L,
# C175F, # very few of these
H179R,
G245S,
WT
)

combined.rho <- unique(as.data.frame(all_grouping))
combined.n <- Pan.final %>%
group_by(P53.Mutation) %>%
summarise(count = (length(P53.Mutation)/138)) # 138 genes per person

# noxes tha should no tbe included into the heatmap
noxes.vector <- c("NOX4", "NOX1", "CYBB", "CYBA", "NOX3", "NOX5", "DUOX1", "DUOX2") # specified order

combined.rho.final <- combined.rho[, !colnames(combined.rho) %in% noxes.vector]

png(paste(deparse(substitute(gene_list_master)), NOX.master, # deparse(substitute()) calls the name of the df as character string
"_byp53_n.png"), width = wid, height = hei, units = 'in', res = dpi)

superheat(
combined.rho.final,
bottom.label.text.angle = 90,
bottom.label.text.size = 3,
scale = F,
grid.hline.col = "white",
grid.vline.col = "white",
grid.hline.size = 1,
grid.vline.size = 1,
pretty.order.rows = T, # unspervised clustering for rows, t= true
pretty.order.cols = T,
left.label.text.alignment = "right",
bottom.label.text.alignment = "right",
heat.pal = c("turquoise", "white", "violetred1"),
bottom.label.size = BLsize,
heat.pal = c("deepskyblue3", "white", "red2"),
heat.lim = c(-1,1),
yr = (combined.n$count),
yr.axis.name = "n of samples",
yr.plot.type = "bar",
legend.breaks = c(-0.8,0,0.8))


dev.off()


}

# for NOX4
Make.heatmap.p53(NOX.master = "NOX4", gene_list_master = EMT.SAbiosci.genes, dpi = 900, wid = 10.5, hei = 6.5)
Make.heatmap.p53.n(NOX.master = "NOX4", gene_list_master = EMT.SAbiosci.genes, dpi = 900, wid = 10.5, hei = 6.5)
Make.heatmap.p53(NOX.master = "NOX4", BLsize = 0.401, gene_list_master = EMT.SAbiosci.genes, dpi = 900, wid = 10.5, hei = 7)

#### NADPHoxidase correlations to genepanels faceted by WT OR MUT (generalized) ----


Make.heatmap.p53.generalized <- function(NOX.master = "NOX4", gene_list_master = EMT.SAbiosci.genes, dpi = 600, wid = 9, hei = 6.5) {
Make.heatmap.p53.generalized <- function(NOX.master = "NOX4", BLsize = 0.401, gene_list_master = EMT.SAbiosci.genes, dpi = 600, wid = 9, hei = 6.5) {

filter.nox.WT <- function(NOX = NOX.master, mutation, gene_list = gene_list_master) {
# outputs the rho of the specificed NOX to the specified genes in the specific p53 mutant group
Expand Down Expand Up @@ -1109,7 +1000,7 @@ Make.heatmap.p53.generalized <- function(NOX.master = "NOX4", gene_list_master =
superheat(
combined.rho.final,
bottom.label.text.angle = 90,
bottom.label.text.size = 3,
bottom.label.text.size = 4,
scale = F,
grid.hline.col = "white",
grid.vline.col = "white",
Expand All @@ -1119,7 +1010,8 @@ Make.heatmap.p53.generalized <- function(NOX.master = "NOX4", gene_list_master =
pretty.order.cols = T,
left.label.text.alignment = "right",
bottom.label.text.alignment = "right",
heat.pal = c("turquoise", "white", "violetred1"),
bottom.label.size = BLsize,
heat.pal = c("deepskyblue3", "white", "red2"),
heat.lim = c(-1,1),
legend = F)

Expand All @@ -1134,7 +1026,7 @@ Make.heatmap.p53.generalized <- function(NOX.master = "NOX4", gene_list_master =
superheat(
combined.rho.final,
bottom.label.text.angle = 90,
bottom.label.text.size = 3,
bottom.label.text.size = 4,
scale = F,
grid.hline.col = "white",
grid.vline.col = "white",
Expand All @@ -1144,7 +1036,8 @@ Make.heatmap.p53.generalized <- function(NOX.master = "NOX4", gene_list_master =
row.dendrogram = F,
left.label.text.alignment = "right",
bottom.label.text.alignment = "right",
heat.pal = c("turquoise", "white", "violetred1"),
bottom.label.size = BLsize,
heat.pal = c("deepskyblue3", "white", "red2"),
heat.lim = c(-1,1),
legend = F)

Expand All @@ -1158,7 +1051,7 @@ Make.heatmap.p53.generalized <- function(NOX.master = "NOX4", gene_list_master =
superheat(
combined.rho.final,
bottom.label.text.angle = 90,
bottom.label.text.size = 3,
bottom.label.text.size = 4,
scale = F,
grid.hline.col = "white",
grid.vline.col = "white",
Expand All @@ -1171,7 +1064,8 @@ Make.heatmap.p53.generalized <- function(NOX.master = "NOX4", gene_list_master =
X.text.col = "grey",
left.label.text.alignment = "right",
bottom.label.text.alignment = "right",
heat.pal = c("turquoise", "white", "violetred1"),
bottom.label.size = BLsize,
heat.pal = c("deepskyblue3", "white", "red2"),
heat.lim = c(-1,1),
legend = F)

Expand All @@ -1183,3 +1077,8 @@ Make.heatmap.p53.generalized <- function(NOX.master = "NOX4", gene_list_master =
# for NOX4
Make.heatmap.p53.generalized(NOX.master = "NOX4", gene_list_master = EMT.SAbiosci.genes, dpi = 900, wid = 10.5, hei = 6.5)

CPCOLS <- c("#2398EB", "#33a02c", "#e31a1c")

ggplot(iris, aes(Sepal.Length, Petal.Length)) +
geom_point(aes(col = Species)) +
scale_colour_manual(values = CPCOLS)

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