R code for cleaning gRNA vs Empty Vector dataset and creating a volcano plot

RNA-Seq_MoreGenes.R

# To download & install BiomaRt package if not previously done
# source("https://bioconductor.org/biocLite.R")
# biocLite("biomaRt")

# Import required packages
require(ggplot2)
require(biomaRt)
require(ggrepel)

# Import the data
rna <- read.csv("data/AllgRNAvsEmptyVector.csv")

# Remove NA values
rna <- na.omit(rna)

# Print first 6 lines
head(rna)
# Reset row numbers
rownames(rna) <- NULL

# Retreive BioMart database
mart <- useDataset("hsapiens_gene_ensembl", useMart("ensembl"))
# Searching BioMart database
genes <- getBM(filters="ensembl_gene_id", 
               attributes=c("ensembl_gene_id", "hgnc_symbol"),
               values=rna$X,
               mart=mart)

# Rename "X" column to "ensembl_gene_id"
colnames(rna)[1] <- "ensembl_gene_id"
# Merging datasets based on ensembl_gene_id
rna_genes <- merge(rna, genes, by="ensembl_gene_id")

# Create plot. Filter out pvalues greater than 0.05, and where -log10(pavlue) greater than 300
ggplot(data=subset(rna_genes, pvalue < 0.05 & -log10(pvalue) <= 300),
       aes(x=log2FoldChange, y=-log10(pvalue))) + 
  xlim(c(-6, 6)) + ylim(c(0, 300)) + # Set axis limits
  geom_point(aes(colour=-log10(pvalue)), size = 3) + # Scatter plot
  scale_color_gradient(low="black", high="red", guide = FALSE) + # Set colour gradient
  geom_label_repel(data=subset(rna_genes, -log10(pvalue) > 180 & -log10(pvalue) < 300), # Add gene name labels and arrows
                  aes(label = hgnc_symbol), 
                  box.padding = 0.5,
                  size=4,
                  force = 2,
                  max.iter = 3e3,
                  point.padding = 1.2,
                  arrow = arrow(length = unit(0.01, "npc"), type="open"), # Add arrows
                  segment.size=0.5) + 
  ggtitle("All gRNA vs Empty Vector") + # Set the title for the plot
  ylab(expression(paste("-log"[10], "(", italic("p"), "-value)"))) + # Y-axis label
  xlab(expression(paste("log"[2], "(fold change)"))) + # X-axis label
  theme_classic() + 
  theme(plot.title=element_text(hjust=0.5)) # Center the title

RNA_Seq.R

# To download & install BiomaRt package if not previously done
# source("https://bioconductor.org/biocLite.R")
# biocLite("biomaRt")

# Import required packages
require(ggplot2)
require(biomaRt)
require(ggrepel)

# Import the data
rna <- read.csv("data/AllgRNAvsEmptyVector.csv")

# Remove NA values
rna <- na.omit(rna)

# Print first 6 lines
head(rna)
# Reset row numbers
rownames(rna) <- NULL

# Retreive BioMart database
mart <- useDataset("hsapiens_gene_ensembl", useMart("ensembl"))
# Searching BioMart database
genes <- getBM(filters="ensembl_gene_id", 
               attributes=c("ensembl_gene_id", "hgnc_symbol"),
               values=rna$X,
               mart=mart)

# Rename "X" column to "ensembl_gene_id"
colnames(rna)[1] <- "ensembl_gene_id"
# Merging datasets based on ensembl_gene_id
rna_genes <- merge(rna, genes, by="ensembl_gene_id")

# Create plot. Filter out pvalues greater than 0.05, and where -log10(pavlue) greater than 300
ggplot(data=subset(rna_genes, pvalue < 0.05 & -log10(pvalue) <= 300),
       aes(x=log2FoldChange, y=-log10(pvalue))) + 
  xlim(c(-6, 6)) + ylim(c(0, 300)) + # Set axis limits
  geom_point(aes(colour=-log10(pvalue)), size = 3) + # Scatter plot
  scale_color_gradient(low="black", high="red", guide = FALSE) + # Set colour gradient
  geom_text_repel(data=subset(rna_genes, hgnc_symbol %in% c("ZEB1")), # Add gene name labels and arrows
                  aes(label = hgnc_symbol), 
                  size=4,
                  point.padding = 1.5,
                  arrow = arrow(length = unit(0.01, "npc"), type="open"), # Add arrows
                  segment.size=0.5) + 
  ggtitle("All gRNA vs Empty Vector") + # Set the title for the plot
  ylab(expression(paste("-log"[10], "(", italic("p"), "-value)"))) + # Y-axis label
  xlab(expression(paste("log"[2], "(fold change)"))) + # X-axis label
  theme_classic() + 
  theme(plot.title=element_text(hjust=0.5)) # Center the title