Hi, I have 19 Salmon.quant sample(9 control,10 cancer)with csv format that merge them with tximport and now want to perform DESeq2 analysis for my merged data to find what transcripts has diffrent expression in cancer and control my sample_key is like this:
NO. group sample
1 control GSM366.
2 control GSM366.
3 control GSM366.
4 cancer GSM366.
5 cancer GSM366.
my txi.salmon is like this:
abundance.GSM366.csv.... counts.GSM366.csv lenght.GSM366.csv
transcript1 0 0 3.25
transcript2 4.61 0.5 3.85
transcript3 0 0 3.26
transcript4 10 1 3.54
....
and these are my R script:
>library(tximport)
>library(readr)
>setwd("G:/Palindrome/salmon_OUT4/")
>SalmonQuantdir<-"G:/Palindrome/salmon_OUT4/Files"
>setwd(SalmonQuantdir)
>files<-list.files(SalmonQuantdir)
>names(files)<-files
>tx2gene<-read.csv("G:/Palindrome/salmon_OUT4/tx2gene.csv")
>txi.salmon <- tximport(files, type="salmon", tx2gene=tx2gene, importer =read.csv, abundanceCol = "TPM")
>Key_file=read.csv("Sample-key.csv")
>library("DESeq2")
but i don't know how to design condition and how to creat countdata and then perform DESeq2. please help me if you know what scripts is appropriate for R?
1 answer
Reading the DESeq2 vignettes and associated workflow are good places to start. They are quite easy to follow and explain each step in-depth to help you understand not only the how, but the why. Your design would just be design = ~ group.
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