I have a Normal esophageal Fibroblasts (NOFs) cultured in DMEM media; The same NOF also have been cultured with a tumor sample from a patient named 005 on DMEM media; I have also Cancer Associated Fibroblasts (CAFs) cultured on DMEM, on DMEM + tumor from a patient named as 005 and DMEM + tumor from a patient named 036 something like this picture;
I want to know if NOF and CAF are different in terms of gene expression but I am not sure about design for DESeq2 or Edger and ANOVA.
By @Devon's help I have done so
> mycols
cell_type co_cultured
G2 NOF NO
G3 NOF YES
G4 CAF NO
G5 CAF YES
G6 CAF YES
dds=DESeqDataSetFromMatrix(countData = NOFCAF,colData = mycols, design =~ cell_type*co_cultured)
Now, I am wondering what would be a suitable contrast for results function in DESeq2
> resultsNames(dds)
[1] "Intercept" "cell_type_NOF_vs_CAF" "co_cultured_YES_vs_NO"
[4] "cell_typeNOF.co_culturedYES"
> res=results(dds)
> res
log2 fold change (MLE): cell typeNOF.co culturedYES
Wald test p-value: cell typeNOF.co culturedYES
DataFrame with 2545 rows and 6 columns
Thanks a lot for correcting me
DESeqDataSetFromMatrix
yourself, you shouldn't need any help (hint:design
is stated incorrectly). $\endgroup$