I am trying to analyse RNASeq data with following design:
dds <- DESeqDataSetFromMatrix(countData = dataCountTable, colData = dataDesign, design = ~ genotype+treatment+genotype:treatment)
dds <- DESeq(dds)
resultsNames(dds)
[1] "Intercept" "genotype_F_vs_C" "genotype_M_vs_C"
[4] "treatment_SAP_vs_GFP" "genotypeF.treatmentSAP""genotypeM.treatmentSAP"
dataDesign
genotype treatment
sample1 F GFP
sample2 F GFP
sample3 F GFP
sample4 F GFP
sample5 F SAP
sample6 F SAP
sample7 F SAP
sample8 F SAP
sample9 M GFP
sample10 M GFP
sample11 M GFP
sample12 M GFP
sample13 M SAP
sample14 M SAP
sample15 M SAP
sample16 M SAP
sample17 C GFP
sample18 C GFP
sample19 C GFP
sample20 C GFP
sample21 C SAP
sample22 C SAP
sample23 C SAP
The question I am trying to answer is:
1. Which genes are DE in male-exposed SAP54 versus male-exposed GFP plants, that are not DE in other comparisons. Meaning these genes should be not DE or significantly less DE or DE in the opposite direction in female-exposed GFP versus female-exposed SAP54 plants, or in male-exposed GFP or non-exposed GFP plants.
2.What does these interaction means genotypeF.treatmentSAP and genotypeM.treatmentSAP?
Any help would be appreciated Thanks!
Thanks Michael. When I do the suggested condition, I get following:
dds <- DESeqDataSetFromMatrix(countData = dataCountTable, colData = dataDesign, design = ~genotype + genotype:treatment)
resultsNames(dds)
[1] "Intercept" "genotype_F_vs_C" "genotype_M_vs_C"
[4] "genotypeC.treatmentSAP" "genotypeF.treatmentSAP" "genotypeM.treatmentSAP"
If I understand correctly "genotypeC.treatmentSAP" : Shows SAP effect on genotypeC
"genotypeF.treatmentSAP" : shows SAP effect on genotypeF
"genotypeM.treatmentSAP" : shows SAP effect on genotypeM
And if I look for genes which are present in genotypeM.treatmentSAP and not in other I can get SAP effect specific to Male. But These genes might be present in genotypeM.treatmentGFP as well. But I am interested in genes which are specific to GFP treatment and should not be there in GFP?
Looking forward for your comment . Thanks!
There is no meaning to "genotypeM.treatmentGFP" in this design.
What you have, genotypeM.treatmentSAP, gives you the treatment effect (SAP vs GFP) for genotype M.
I'm suggesting to build three results tables, using results(dds, name="genotypeM.treatmentSAP") etc.
Then find the set of genes that are in the M comparison but not in the others. This is the best you can do, there isn't a single contrast that will produce the set that you're looking for.
Thanks Michael. I think I understand intersection now. Much appreciated!