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TNMplot.Rmd
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TNMplot.Rmd
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---
title: "Breast Cancer, gene expression in Tumor, Normal, and Metastatic samples"
author: "Mikhail Dozmorov"
date: "`r Sys.Date()`"
output:
pdf_document:
toc: no
html_document:
toc: no
theme: united
bibliography: data.TCGA/TCGA.bib
csl: styles.ref/genomebiology.csl
editor_options:
chunk_output_type: console
---
```{r setup, echo=FALSE, message=FALSE, warning=FALSE}
# Set up the environment
library(knitr)
opts_chunk$set(cache.path='cache/', fig.path='img/', cache=T, tidy=T, fig.keep='high', echo=F, dpi=100, warnings=F, message=F, comment=NA, warning=F, results='as.is', fig.width = 10, fig.height = 6) #out.width=700,
library(pander)
panderOptions('table.split.table', Inf)
set.seed(1)
library(dplyr)
options(stringsAsFactors = FALSE)
```
```{r}
library(curatedTCGAData)
library(TCGAutils)
library(ggplot2)
library("ggsci")
library(scales)
# scales::show_col(pal_lancet("lanonc")(8))
mycols = pal_lancet("lanonc")(8)
library(grid)
library(gridExtra)
library(ggprism)
```
```{r echo=TRUE}
selected_genes <- c("MYC")
```
```{r results='hide'}
brca <- curatedTCGAData(diseaseCode = "BRCA", assays = "RNASeq2GeneNorm", FALSE, version = "2.0.1")
# https://gdc.cancer.gov/resources-tcga-users/tcga-code-tables/sample-type-codes
# 01 Primary Solid Tumor
# 11 Solid Tissue Normal
sampleTables(brca)
# 01 06 11
# 1093 7 112
```
# Tumor-normal pairs comparison
```{r message=FALSE, results='hide'}
(tnmae <- splitAssays(brca, c("01", "11")))
(matchmae <- as(tnmae, "MatchedAssayExperiment"))
selected_expr_tumor <- assay(matchmae[[1]])[selected_genes, ]
selected_expr_normal <- assay(matchmae[[2]])[selected_genes, ]
# T-test to put on a plot
res <- t.test(selected_expr_normal, selected_expr_tumor, paired = TRUE)$p.value
grob <- grobTree(textGrob(paste0("p-value: ", formatC(res, format = "e")), x=0.1, y=0.90, hjust=0, gp=gpar(col="black", fontsize=10, fontface="italic")))
mtx_to_plot <- data.frame(Status = c(rep("Tumor", length(selected_expr_tumor)), rep("Normal", length(selected_expr_normal))), Expression = c(selected_expr_tumor, selected_expr_normal))
# ggplot(mtx_to_plot, aes(x = Status, y = Expression, fill = Status)) +
# geom_boxplot() +
# theme_bw() +
# scale_fill_manual(values = mycols[c(3, 2, 1)]) +
# geom_jitter(shape=20, position=position_jitter(0.2), size = 1, alpha = 0.2) +
# annotation_custom(grob)
```
```{r fig.height=4, fig.width=4}
p1 <- ggplot(mtx_to_plot, aes(x = Status, y = Expression, fill = Status)) +
geom_boxplot() +
scale_fill_prism(palette = "prism_light") +
geom_jitter(shape=20, position=position_jitter(0.2), size = 1, alpha = 0.2) +
annotation_custom(grob) +
theme_prism(palette = "prism_light")
ggsave("results/Figure_TN_paired.png", plot = p1, width = 4, height = 4, dpi = 300)
```
# Tumor-normal-metastatic comparison
```{r message=FALSE, results='hide'}
(tnmae <- splitAssays(brca, c("01", "11", "06")))
selected_expr_tumor <- assay(tnmae[[1]])[selected_genes, ]
selected_expr_met <- assay(tnmae[[2]])[selected_genes, ]
selected_expr_normal <- assay(tnmae[[3]])[selected_genes, ]
mtx_to_plot <- data.frame(Status = c(rep("Tumor", length(selected_expr_tumor)), rep("Normal", length(selected_expr_normal)), rep("Metastatic", length(selected_expr_met))), Expression = c(selected_expr_tumor, selected_expr_normal, selected_expr_met))
mtx_to_plot$Status <- factor(mtx_to_plot$Status, levels = c("Normal", "Tumor", "Metastatic"))
res_tn <- t.test(selected_expr_tumor, selected_expr_normal)$p.value %>% formatC(., format = "e")
res_tm <- t.test(selected_expr_tumor, selected_expr_met)$p.value %>% formatC(., format = "e")
res_mn <- t.test(selected_expr_met, selected_expr_normal)$p.value %>% formatC(., format = "e")
grob <- textGrob(paste0("T vs. N: ", res_tn, ", T vs. M: ", res_tm, ", M vs. N: ", res_mn)) #, gp=gpar(col="black", fontsize=8, fontface="italic")))
my_text <- paste0("T vs. N: ", res_tn, ", T vs. M: ", res_tm, ", M vs. N: ", res_mn)
my_grob <- grid.text(my_text, x=0.5, y=0.9, gp=gpar(col="black", fontsize=6, fontface="italic"))
# ggplot(mtx_to_plot, aes(x = Status, y = Expression, fill = Status)) +
# geom_boxplot() +
# theme_bw() +
# scale_fill_manual(values = mycols[c(3, 2, 1)]) +
# geom_jitter(shape=20, position=position_jitter(0.2), size = 1, alpha = 0.2) +
# annotation_custom(my_grob)
```
```{r fig.height=4, fig.width=5}
p2 <- ggplot(mtx_to_plot, aes(x = Status, y = Expression, fill = Status)) +
geom_boxplot() +
# scale_fill_prism(palette = "prism_light") +
scale_fill_manual(values = c(prism_color_pal(palette = "prism_light")(10)[6], prism_color_pal(palette = "prism_light")(10)[7], prism_color_pal(palette = "prism_light")(10)[9])) +
geom_jitter(shape=20, position=position_jitter(0.2), size = 1, alpha = 0.2) +
annotation_custom(my_grob) +
theme_prism(palette = "prism_light")
ggsave("results/Figure_TNM.png", plot = p2, width = 5, height = 4, dpi = 300)
```
```{r fig.height=4}
grid.arrange(p1, p2, ncol = 2)
```
```{r eval=FALSE}
library(scales)
show_palette <- function(palette) {
scales::show_col(
prism_colour_pal(palette = palette)(
attr(prism_colour_pal(palette = palette), "max_n")
)
)
}
# show the colours in the palette "pearl"
show_palette("prism_light")
```