Hi,
thanks for the cool package, it's been useful and easy to use so far!
I have a control condition and three "treatment" conditions, and I'd like to compare each treatment to control. My condition metadata column is set up as a factor with four levels. I can't figure out how to specify the appropriate contrast as an argument to de_test_neighbourhoods. The documentation for de_test_neighbourhoods says this should be a string, and to look at the edgeR docs for the syntax. In the edgeR docs I see two ways of specifying contrasts: using makeContrasts, or as a numeric vector.
I tried contrasts = "Treat1-Control" by extrapolating from the makeContrasts syntax, but this gave me the following error:
Quitting from lines 267-280 (miloDE.Rmd)
Error in glmFit.default(y, design = design, dispersion = dispersion, offset = offset, :
Design matrix not of full rank. The following coefficients not estimable:
ConditionTreat1 ConditionTreat2 ConditionTreat3
Any suggestions about what I should be putting instead? I really couldn't find any section in the edgeR docs where they specify contrast as a string. A section reference or an example would be really helpful.
Hi,
thanks for the cool package, it's been useful and easy to use so far!
I have a control condition and three "treatment" conditions, and I'd like to compare each treatment to control. My condition metadata column is set up as a factor with four levels. I can't figure out how to specify the appropriate contrast as an argument to
de_test_neighbourhoods. The documentation forde_test_neighbourhoodssays this should be a string, and to look at the edgeR docs for the syntax. In the edgeR docs I see two ways of specifying contrasts: usingmakeContrasts, or as a numeric vector.I tried
contrasts = "Treat1-Control"by extrapolating from themakeContrastssyntax, but this gave me the following error:Any suggestions about what I should be putting instead? I really couldn't find any section in the edgeR docs where they specify contrast as a string. A section reference or an example would be really helpful.