I followed the PICRUSt2 pipeline and obtained the
ko_metagenome.qza, which contained more than 8000 KOs in with absolute abundance (I think is absolute). When I ran the ANCOM test:
qiime composition add-pseudocount \ --i-table picrust2_output/ko_metagenome.qza \ --o-composition-table ko_metagenome-added.qza qiime composition ancom \ --i-table ko_metagenome-added.qza \ --p-transform-function log \ --m-metadata-file metadata.tsv \ --m-metadata-column Group \ --o-visualization ANCOM.qzv
The work was stuck because I think my mac (16G memories) is not able to run it (8000 KOs, 40 samples in the table). My first question: is there an alternative way severing similar function as ANCOM but require less resource of the computer?
I also tried another way myself, I scale the table by
total sum scaling, which is: the sum of all KOs in a sample is 1. After that, I calculated the
Fold change of every KOs and tested the significant by T-test with adjust p-value. The distint KOs were visualised by a volcano plot.
It’s a very simple way to compare distinct KOs as well as OTUs in a compositional table. However, I am not sure whether it is appropriate to calculate Fold changed and do the testing from the relative abundance of the KOs.
My second question is: Is it ok to calculate the Fold change of the features and do the testing by their relative abundance? Any better scaling or normalisation of the data table should I do？
Thanks for all the advices