File size: 1,433 Bytes
90f526e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 |
#
# Transform feature counts output to simple counts.
#
# The results files to be compared.
# Count file produced by featurecounts.
counts_file <- "counts.txt"
# The sample file must be in CSV format and must have the headers "sample" and "condition".
design_file = "design.csv"
# The name of the output file.
output_file = "counts.csv"
# Inform the user.
print("# Tool: Parse featurecounts")
print(paste("# Design: ", design_file))
print(paste("# Input: ", counts_file))
# Read the sample file.
sample_data <- read.csv(design_file, stringsAsFactors=F)
# Turn conditions into factors.
sample_data$condition <- factor(sample_data$condition)
# The first level should correspond to the first entry in the file!
# Required when building a model.
sample_data$condition <- relevel(sample_data$condition, toString(sample_data$condition[1]))
# Read the featurecounts output.
df <- read.table(counts_file, header=TRUE)
#
# It is absolutely essential that the order of the featurecounts headers is the same
# as the order of the sample names in the file! The code below will overwrite the headers!
#
# Subset the dataframe to the columns of interest.
counts <- df[ ,c(1, 7:length(names(df)))]
# Rename the columns
names(counts) <- c("name", sample_data$sample)
# Write the result to the standard output.
write.csv(counts, file=output_file, row.names=FALSE, quote=FALSE)
# Inform the user.
print(paste("# Output: ", output_file))
|