Hi
I have a question regarding RNAseq data analyses by DESeq2,
I have some data with 3 conditions (A, A1, D) and 3 other factors (P, B, Sex) with 2 or 3 levels in each,
my question is that if I use LRT without any contrast, is that correct to imply whatever results give me as a final output for comparison across these 3 levels in my condition,
I used this code:
ddsMF <- DESeq(dds, test="LRT", reduced = ~ P + B + Sex, parallel=TRUE) summary(ddsMF) res_A_D_July17_ncon <- results(ddsMF)
2- if not, how a two-way comparison of DESeq2 is able to tell me how different the 3 conditions are from each other,
I mean if I use A vs D, A1 vs D, A vs A1, what is the big picture to see all the differences across all the 3 levels of condition.
Thanks,
Hi Michael,
Thanks for the reply, I would appreciate your help.
our question is that considering 3 factors other than condition (3 levels, A, A1, D) which includes sex, passage of cells and different batches of expermint, what are the differntially expressed genes across all our samples (35, 14 D, 8 A1, and 13 of A). how different our samples are in terms of gene expression,
here is my full design,
dds <- DESeqDataSetFromMatrix ( countData = cts,
colData = sampleinfo_July17,
design = ~ B + P + Sex + condition )
ddsMF <- DESeq(dds, test="LRT", reduced = ~ P + B + Sex, parallel=TRUE)
summary(ddsMF)
(is this code necessary for looking at all the samples? as its just paired-wise comaprison) res_A_D_July17 <- results(ddsMF, contrast=c("condition","A","D"))
res_A_D_July17
mcols(res_A_D_July17, use.names = TRUE)
summary(res_A_D_July17) # summarize some basic tallies
resultsNames(ddsMF) # lists the coefficients
resultsNames(ddsMF) # lists the coefficients
[1] "Intercept" "B_B2_vs_B1" "B_B3_vs_B1"
[4] "B_B4_vs_B1" "P_R_vs_q" "Sex_M_vs_F"
[7] "condition_A_vs_D" "condition_A1_vs_D"
>
So getting back to the first question, yes the LRT here is testing across all levels of the condition variable.
See the sections of the help page ?results and the FAQ in the vignette about why only one coefficient is shown with the LRT.
You can see all the coefficients in the model with coef(dds) but the LRT represents a test of multiple coefficients here.