| # | |
| # 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)) | |