Hello,
I have a RNAseq experiment where I have 2 conditions and 3 replicates each and replicates are taken from different individuals. So my design is as follows:
Sample Condition Individual
S1 treated A
S2 untreated A
S3 treated B
S4 untreated B
S5 treated C
S6 untreated C
Here is my code to analyse the data using deseq2:
However, when I run these and look at results, following message:
So, its only giving me results after comparing C vs A. Am I missing anything here?
Thanks for any help.
I have a RNAseq experiment where I have 2 conditions and 3 replicates each and replicates are taken from different individuals. So my design is as follows:
Sample Condition Individual
S1 treated A
S2 untreated A
S3 treated B
S4 untreated B
S5 treated C
S6 untreated C
Here is my code to analyse the data using deseq2:
Code:
library('DESeq2') directory<-"counts" sampleFilesN1_N2 <- grep("*N[1-2]",list.files(directory),value=TRUE) sampleConditionN1_N2<-c("treated","untreated","treated","untreated","treated","untreated") sampleIndividual<-c("A","A","B","B","C","C") sampleTable1<-data.frame(sampleName=sampleFilesN1_N2, fileName=sampleFilesN1_N2, condition=sampleConditionN1_N2, individual=sampleIndividual) ddsHTSeq <- DESeqDataSetFromHTSeqCount(sampleTable = sampleTable1, directory = directory,design= ~ condition + individual) ddsHTSeq$condition <- relevel(ddsHTSeq$condition, "untreated") dds<-DESeq(ddsHTSeq) res<-results(dds) res<-res[order(res$padj),] write.csv(as.data.frame(res),file="DeSEQ2_treated_vs_untreated.csv")
Code:
"log2 fold change (MAP): individual C vs A Wald test p-value: individual C vs A"
Thanks for any help.
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