Hi everyone,

I have 12 samples - 3 Controls, 3 T1 , 3 T2 and 3 T3. I am interested in looking at genes that are different between controls and treatment. Also I would like to obtain DE genes that are different between control average and treatment average for which I had provided the contrast above that I want from the analysis (T1 + T2 + T3)/3 - Controls. I am unable to input such contrasts in the test_differential_abundance function under the contrasts argument. Can you suggest the design and contrasts arguement for looking at control vs treatments and controls average versus treatment average.

Thank you Adi

For edgeR and Voom

if your column is called treatment then the contrast argument would be

contrast = "(treatmentT1 + treatmentT2 + treatmentT3)/3 - treatmentControls"

For DESeq2

you provide a contrast = list(...), in the same way you do for DESeq2

Some examples from the tidybulk documentation below.

@examples
 # edgeR

 tidybulk::se_mini |>
 identify_abundant() |>
    test_differential_abundance( ~ condition )

    # The function `test_differential_abundance` operates with contrasts too

 tidybulk::se_mini |>
 identify_abundant() |>
 test_differential_abundance(
        ~ 0 + condition,
        contrasts = c( "conditionFALSE - conditionTRUE")
 )

 # DESeq2 - equivalent for limma-voom

my_se_mini = tidybulk::se_mini
my_se_mini$condition  = factor(my_se_mini$condition)

my_se_mini  |>
 identify_abundant() |>
    test_differential_abundance( ~ condition, method="deseq2" )

    # The function `test_differential_abundance` operates with contrasts too

 my_se_mini |>
 identify_abundant() |>
 test_differential_abundance(
        ~ 0 + condition,
        contrasts = list(c("condition", "FALSE", "TRUE")),
        method="deseq2"
 )