Hi, I have used the rnaseq nextflow pipeline to generate count tables from 9 samples of this GEO dataset:

https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE134127,

There are 18 samples, 9 exposed to a chemical compound and 9 unexposed, I have chosen the 9 unexposed samples as they are of interest to me for a project; the samples appear in SRA like this:

https://www.ncbi.nlm.nih.gov/Traces/study/?acc=PRJNA554005&f=source_name_sam_ss%3An%3Amock-treated%3Ac&o=acc_s%3Aa

My goal is to do a differential expression analysis between these samples and obtain a volcano plot and a heatmap with DESeq2.

I understand that DESeq2 in order to generate a volcano plot and heatmap, needs to generate a matrix counts that can be generated from a previous matrix or a tximport object containing the rounded counts, for example, from a matrix:

dds <- DESeqDataSetFromMatrix(countData = counts_as_matrix,
                              colData = samplesheet_metadata_SRA,
                              design= ~ condition) # This is where i do not know what to assign

I have managed to generate a matrix object with the counts of my samples, but I have doubts about the colData and design arguments, because I don't know if they are right.

For example this is how a part of my file that should go in colData looks like, which is basically the SRA metadata file of the 9 samples I have mentioned, I show 3 of the 9 samples, which all have the same characteristics for source_name, tissue, etc.

My biggest doubt is regarding the design argument in the function DESeqDataSetFromMatrix, what should I put there? as you can see in the metadata table, all the samples are mock-treated.

Thank you for your help and time