Which DeSeq2 study design to use when there is data from controls and two different disease states (moderate and high) and stage level (1,2,3)? And how to create a sumarized experiment out of it?

Question

[salman_96]

Hi, I have to run Differential expression using DESeq2. I have count data file and a file with sample information.

I have to analyze DEGs between the disease state (INFECTION STATUS) "cases and controls" but I have additional information regarding the state of the disease which is early and moderate for cases. I have tried to look for what kind of study design would I create for the Deseq2 analysis but I am unable to find any help. I will really appreciate the hepl
I have tried to add some info in a data frame from the sample information/colData file. The colData is below:

    run <-c("SRR123", "SRR112","SRR433","SRR666","SRR342", "SRR564")

disease_stage<- c(1,1,2,3,0,0)

STAGE <- c("early","early","moderate","moderate","control", "control")

geo_id<-c("GSM123","GSM333","GSM444","GSM153","GSM113","GSM434")
disease<- c("Yes","Yes","Yes","Yes","Control","Control")
coldata_df <- data.frame(run,disease_stage,STAGE,geo_id, disease)
coldata_df

And a sample counts data is shown below:

SRR123<-c(123,24,35,22,55,77)
SRR112<-c(21,64,287,85,23,34)
SRR433<-c(33,55,77,33,45,77)
SRR666<-c(77,66,99,36,85,36)
SRR342<-c(32,8,35,76,24,77) 
SRR564<-c(43,3,77,9,456,7)
gene<-c("ESN2","ESN3","ESN4","ESN6","ESN7","ESN8")
counts=data.frame(gene,SRR123,SRR112,SRR433,SRR666,SRR342,SRR564)

I will really appreciate your response

Regards, Salman

Answer 1

[rpolicastro]

You should make a combined factor level, such as:

sample_type <- c("disease_early", "disease_early", "disease_moderate", "disease_moderate", "control", "control")
sample_type <- relevel(factor(sample_type), "control")

Your regression design would be ~ sample_type

Your controls aren't broken down into early or moderate like the disease samples are, and you have only an n of 2 per group, so I wouldn't really recommend any more complicated of a design.