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At some stage those 6 .txt files will need to be combined into a single data frame (table) for DESeq analysis. You could do this beforehand in python or bash, or after importing them into R.
If you're not familiar with scripting perhaps the easiest would be to import each file separately in R:
count_sample1 <- read.csv("/home/work/HTSeq/htseqresults/sample1.txt", sep="\t", row.names=1)
colnames(count_sample1) <- "sample1"
count_sample2 <- read.csv("/home/work/HTSeq/htseqresults/sample2.txt", sep="\t", row.names=1)
colnames(count_sample2) <- "sample2"
etc.
Then combine them into a data frame using merge:
combined_counts <- merge(count_sample1, count_sample2, etc., by=row.names)
Something like this should work depending on the HTSeq output format. Check the R help pages for "read.csv" and "merge" for further info.
Good luck!
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TopHat-HTSeq-DESeq pipeline (HELP PLEASE!)
Hello all,
I am having an issue with importing my information(6 .txt files) within the directory using Linux and R. The pipeline that I am using is TopHat-HTSeq-DESeq. This may be simple, however, I am no expert. I have 6 .txt files in a directory called htseqresults. Within that directory, I go to R (by typing R). The following is what I attempted:
>library(DESeq)
> datafile<-system.file(path="/home/work/HTSeq/htseqresults")
> datafile
[1] ""
I attempted to use the Differential expression of RNA-Seq data at the gene level –the DESeq package. The data is not stored in my computer, instead is stored in the server. How will I be able to import these 6 .txt files? Is it possible to do collectively? Do I have to import each at one time?
Please help.
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