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deg_and_volcanos.Rmd
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deg_and_volcanos.Rmd
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---
title: "DEG and Volcano Plots"
author: "Matthew Angel"
date: "7/28/2021"
output:
html_document: default
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
## Deg Analysis
```{r deg, echo=TRUE}
suppressMessages(library(limma))
suppressMessages(library(tidyverse))
suppressMessages(library(edgeR))
suppressMessages(library(stringr))
suppressMessages(library(DT))
suppressMessages(library(EnhancedVolcano))
suppressMessages(library(cowplot))
suppressMessages(library(gridExtra))
workDir <- '/Users/angelmg/Documents/nci_vb_git/bergamaschi_pfizer_cancer'
setwd(workDir)
#Read in data
df <- read.delim(file = file.path(workDir,"output","processed_data.csv"), sep = ',',
header = TRUE)
targetfile <- read.delim(file = file.path(workDir,"output","sample_annot.csv"), sep = ',',
header = TRUE, row.names = 1)
genenames <- rownames(df)
samples_for_deg_analysis = targetfile$sample_id #include everyone
df.m <- df[,samples_for_deg_analysis]
gene_names <- NULL
gene_names$GeneID <- rownames(df)
targetfile <- targetfile[match(colnames(df.m),targetfile$sample_id),] #just make extra sure
y <- df.m[,match(targetfile$sample_id,colnames(df.m))]
ordered_covariates=c("timepoint","patient_id")
ordered_covariates=ordered_covariates[order(ordered_covariates!="timepoint")]
targetfile <- targetfile %>% select(sample_id,one_of(ordered_covariates)) %>% as.data.frame()
row.names(targetfile) <- targetfile$sample_id
dm.formula <- as.formula(paste("~0 +", paste(ordered_covariates, sep="+", collapse="+")))
design=model.matrix(dm.formula, targetfile)
colnames(design) <- str_replace_all(colnames(design), "timepoint", "")
out <- list()
y <- as.matrix(y)
out$E <- y
out$design <- design
v <- new("EList", out)
rownames(v$E) <- genenames
as.data.frame(v$E) %>% rownames_to_column("Gene") -> df.voom
fit <- lmFit(v, design)
contrasts_of_interest <- c( "d2-d1",
"d23-d22",
"(d23-d22)-(d2-d1)")
cm <- makeContrasts(contrasts = contrasts_of_interest, levels=design)
fit2 <- contrasts.fit(fit, cm)
fit2 <- eBayes(fit2)
logFC = fit2$coefficients
colnames(logFC)=paste(colnames(logFC),"logFC",sep="_")
tstat = fit2$t
colnames(tstat)=paste(colnames(tstat),"tstat",sep="_")
FC = 2^fit2$coefficients
FC = ifelse(FC<1,-1/FC,FC)
colnames(FC)=paste(colnames(FC),"FC",sep="_")
pvalall=fit2$p.value
colnames(pvalall)=paste(colnames(pvalall),"pval",sep="_")
pvaladjall=apply(pvalall,2,function(x) p.adjust(x,"BH"))
colnames(pvaladjall)=paste(colnames(fit2$coefficients),"adjpval",sep="_")
deg_results=as.data.frame(cbind(FC, logFC, tstat, pvalall, pvaladjall))
deg_results %>% rownames_to_column("Gene") -> deg_results
write.table(deg_results, file=file.path(workDir,"output","deg_analysis.tsv"), sep="\t", row.names = FALSE)
print(paste0("Total number of genes included: ", nrow(deg_results)))
call_me_alias<-colnames(deg_results)
colnames(deg_results)<-gsub("\\(|\\)","",call_me_alias)
p = htmltools::tagList()
grobsList <- vector(mode = "list", length = length(contrasts_of_interest))
for(i in seq_along(contrasts_of_interest)){
contrast <- contrasts_of_interest[i]
contras <- unlist(str_split(contrast,"-"))
if(length(contras) > 2){
contras[1] <- paste(contras[1:2],collapse="-")
contras[2] <- paste(contras[3:4],collapse="-")
contras <- contras[1:2]
contras <- gsub("\\(|\\)","",contras)
}
columns_of_interest <- c("Gene",grep(paste0("^",contrast,"_"),colnames(deg_results),value=TRUE))
label.col <- "Gene"
lfc.col <- grep("_logFC",columns_of_interest,value=TRUE)
sig.col <- grep("_pval",columns_of_interest,value=TRUE)
deg_sorted <- deg_results %>% select(one_of(columns_of_interest)) %>% arrange(!!rlang::sym(sig.col))
p[[i]] <- DT::datatable(deg_sorted, extensions = 'Responsive', caption=htmltools::tags$caption(paste0("DEG Statistics for contrast: ",contras[1],"_vs_",contras[2]) ,style="color:gray; font-size: 18px" ),rownames=F, width = "100%", height = "auto")
columns_of_interest <- c(label.col,lfc.col,sig.col)
deg_sorted <- deg_sorted[,columns_of_interest]
change_lfc_name <- "log2FC"
change_sig_name <- "pvalue"
colnames(deg_sorted) <- c(label.col,change_lfc_name,change_sig_name)
value_to_sort_the_output_dataset <- "p-value"
if (value_to_sort_the_output_dataset=="fold-change") {
deg_sorted %>% dplyr::arrange(desc(abs(!!rlang::sym(change_lfc_name)))) -> deg_sorted
} else if (value_to_sort_the_output_dataset=="p-value") {
deg_sorted %>% dplyr::arrange(!!rlang::sym(change_sig_name)) -> deg_sorted
}
no_genes_to_label <- 15
genes_to_label <- as.character(deg_sorted[1:no_genes_to_label,label.col])
# Plot variables
title <- "Volcano Plot"
subtitle <- paste0(contras[1]," vs ",contras[2])
pCutoff = 0.05
FCcutoff = 1.0
significant=as.vector(table(abs( deg_sorted[,change_lfc_name] ) > FCcutoff &
deg_sorted[,change_sig_name] < pCutoff))[2]
maxy <- ceiling(max(-log10(deg_sorted[[change_sig_name]]), na.rm=TRUE))
xlab <- bquote(~Log[2]~ "fold change")
xlim_additional <- 0
ylim_additional <- 0
axisLabSize <- 24
labSize <- 4
pointSize <- 2
imageWidth = 3000
imageHeight = 3000
dpi = 300
filename=file.path(workDir,"plots",paste0("volcano_",contras[1],"_vs_",contras[2],".png"))
png(
filename = filename,
width=imageWidth,
height=imageHeight,
units="px",
pointsize=4,
bg="white",
res=dpi,
type="cairo")
vp <- EnhancedVolcano( deg_sorted,x=change_lfc_name,y=change_sig_name,
lab=deg_sorted[,label.col],
selectLab = genes_to_label,
title=paste0(title," (Significant=",significant,")"),
subtitle <- subtitle,
xlab=xlab,
ylab=bquote(~-Log[10]~.(change_sig_name)),
xlim=c(floor(min(deg_sorted[,change_lfc_name])) - xlim_additional,ceiling(max(deg_sorted[,change_lfc_name]))+ xlim_additional),
ylim=c(0, maxy + ylim_additional),
pCutoff=pCutoff,
FCcutoff=FCcutoff,
axisLabSize=axisLabSize,
labSize=labSize,
pointSize=pointSize)
print(vp)
dev.off()
grobsList[[i]] <- vp
}
grobs <- arrangeGrob(grobs=grobsList,ncol=1,newpage=F)
```
```{r fig.width=10, fig.height=30,echo=FALSE}
plot(grobs)
```
```{r deg_tables, echo=TRUE}
p
```
```{r session, echo=FALSE}
sessionInfo()
```