Normalisation & Parallel Computing for mbImpute

[RishBez]

Greetings mbImpute Team!

I have been trying to utilise the mbImpute method for a microbiome dataset with OTU counts provided for various samples. Pardon my ignorance, but since this is a new domain I am working in, I was wondering if I need to apply normalisation procedures before utilizing mbImpute( ) or if setting the 'unnormalised' to TRUE would be sufficient (default normalisation procedures outlined in your paper)?

The reason I am asking you this is that the dataset contains over 2,000 samples with over 100 OTU variables, and 2 metadata variables (excluding the study-condition variable). The observations are the raw OTU counts. It might be due to the size of the dataset, however, the function has still not finished running after 24 hours - so I wanted to check if I am taking the correct path.

Additionally, do I need to initiate extra packages to leverage parallel processing in the mbImpute( ) function?