Hi,

Im running tradeseq with a dataset of ~25k cells and 130 samples so computation time and memory to run fitGAM are going to be an issue for me. With respect to that I have seen reccomendations to reduce the number of genes put into the function just to the top 2k variable features, however can I clarify - is that reducing the whole counts matrix down to 2k features, or keeping the whole counts matrix and putting the names of the top 2k variable features into the genes argument?

Thanks, Matt

Hi,

We recommend keeping the entire count matrix and using the genes argument. This way, you still use the data from all genes to do the normalization.