After reading this post and this page I would like some clarification for results(). For exemplification, I am will be referring to the webpage.
1a) In "Example 1 : two-group comparison" what would be the difference between the following codes?
results(dds, contrast=c("condition", "B", "A")
results(dds, name="condition_B_vs_A")
From my understanding the lfc (countData B / countDataA) is the same for both
1b) In "Example 2: two conditions, two genotypes, with an interaction term (The effect of treatment in wild-type (the main effect)", what would be the difference between the following codes?
results(dds, contrast=c("condition", "Trt", "Ctrl"))
results(dds, name="condition_Trt_vs_Ctrl")
2a) In "Example 2: two conditions, two genotypes, with an interaction term (The effect of treatment in wild-type (the main effect)", treatment effect across all genotypes or just "wt"?
res = results(dds, contrast=c("condition","Trt","Ctrl"))
I would think that this contrast would compare the effects of "Trt" and "Ctrl" across all genotypes, but in the text below it states that this contrasts the effect in only "wt" because we set the reference. A one word answer would suffice
2b) In "Example 2: two conditions, two genotypes, with an interaction term (The effect of treatment in wild-type (the main effect)" is there a method on retrieving the SDG from the effect of treatment across all samples?
For the data I am analysing I would like to see the effects of a treatment across all samples , using the untreated version of said sample as reference. (i.e) I hope to get the SDG of treatment by comparing HeyA8-QC with HeyA8-DMSO, HeyA8MDR-QC and HeyA8MDR-DMSO, etc.
sample_id treatment
1 HeyA8 DMSO
2 HeyA8_MDR DMSO
3 HeyA8_MDR QC
4 HeyA8 QC
5 SKOV3 DMSO
6 SKOV3 QC
7 TR DMSO
8 C13 DMSO
9 C13 QC
10 HeyC2 DMSO
11 HeyC2 QC
12 OV2008 DMSO
13 OV2008 QC
14 TR QC
You need to add what the design is for your examples, as adding the interaction term changes the meaning of some of the examples. I strongly recommend making a dummy data set as the second link shows, getting the normalized counts, and confirming in Excel what all the different kinds of contrasts do.
Thank you for the reply, but all the questions except for 2b are referring the webpage I linked. As for 2b I wasn't too sure on what order I wanted the design in (you gave a reply to this question in my previous post). However, for clarification here would be my design.
EDIT: Also how would I get a descriptive idea on differing contrasts from numerical data? Moveover how would I find these differences in the sea of numbers?