Entering edit mode
7.7 years ago
pennakiza
▴
60
Hello all,
RNA-seq DE analysis noob here so please bear with my silly question!
So, I have tximported my salmon data of paired-end RNA seq reads and I am trying to use DESeq2 to analyze the differential expression for two conditions (screen and treatment) in 8 different patients.
I use this bit of code:
coldata<-data.frame(con=s2c$condition)
rownames(coldata)<-colnames(txi)
dds <- DESeqDataSetFromTximport(txi, colData=coldata, design= ~con)
dds <- dds[ rowSums(counts(dds)) > 1, ]
dds<-DESeq(dds)
res<-results(dds)
but I get padj values in all my genes around 0.9!
On the other hand, if I use replicates (patient1, patient2 and so on) I got some significant padjs but my MA plot is a small vertical line!
Maybe I shouls use both factors (replicate and condition) on my design? How can I do that?
Could someone please help me understand what I am doing wrong?
Thank you very much!
Pen
What do you mean by "if I use replicates"? I presume there are replicates in the example you posted.
I mean if I use replicates as a comparison in design, instead of condition. So if instead of comparing "treated" and "screen" samples, I compare "patient 1" to "patient 2" and so on, regardless the condition?
1) please list all the samples names and the organism they come from. 2) then tell us what you are comparing
So, my table looks like that: [https://ibb.co/npWGfa]
where replicates is the patient the sample comes from, so P1= patient 1, P2= patient2 and so on. They are samples from human cancer patients, taken before and after treatment.
What I am looking for is to compare the gene expression between the patients, before and after treatment.
Were you able to find a solution to this? I am in a similar situation with my data currently!