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#
# Combine transcripts with the tximport package.
#
# https://bioconductor.org/packages/release/bioc/html/tximport.html
#
# Transcript level summarization.
#
# Load the packages
library(tximport)
# The directory where the counts for each sample are located.
data_dir <- 'salmon'
# The sample file must be in CSV format and must have the headers "sample" and "condition".
desing_file = "design.csv"
# What software created the mappings.
method <- "salmon"
# The output file name.
output_file = "counts.csv"
# Inform the user.
print("# Tool: Combine transcripts")
print(paste("# Sample: ", desing_file))
print(paste("# Data dir: ", data_dir))
# Read the sample file
sample_data <- read.csv(desing_file, stringsAsFactors=F)
# Isolate the sample names.
sample_names <- sample_data$sample
# Generate the file names that contain the quantification data.
files <- file.path(data_dir, sample_names, "quant.sf")
# Summarize over transcripts.
tx <- tximport(files, type=method, txOut=TRUE)
# Transform counts into a dataframe.
df <- data.frame(tx$counts)
# Set the column names.
colnames(df) <- sample_names
# Create a new column for transcript ids.
df$ensembl_transcript_id = rownames(df)
# List the desired column order.
cols <- c("ensembl_transcript_id", sample_names)
# Reorganize the columns.
df <- df[, cols]
# Save the resulting summarized counts.
write.csv(df, file=output_file, row.names = FALSE, quote = FALSE)
# Inform the user.
print(paste("# Results: ", output_file))
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