Hi,
I want to use metagenomeSeq for DA analysis for a dataset that has already been normalized according to an internal standard in the library. That means, that I am interested not only in relative changes but also in absolute changes of reads (abundances) between different treatments in my experiment. I would like to know if the model implemented in fitFeatureModel() can be used with this quantitative approach of feature counts without any normalization. Since fitFeatureModel() requires the normFactors slot to be filled, would it be appropriate for my approach to add a constant integer of size equal to number of samples? (eg, normFactors(obj) <- rep(1, ncol(obj)))
Thanks
Hi, I want to use metagenomeSeq for DA analysis for a dataset that has already been normalized according to an internal standard in the library. That means, that I am interested not only in relative changes but also in absolute changes of reads (abundances) between different treatments in my experiment. I would like to know if the model implemented in
fitFeatureModel()can be used with this quantitative approach of feature counts without any normalization. SincefitFeatureModel()requires thenormFactorsslot to be filled, would it be appropriate for my approach to add a constant integer of size equal to number of samples? (eg,normFactors(obj) <- rep(1, ncol(obj))) Thanks