Thanks for the quick reply ! To add information to my initial query. I actually filtered my BIOM table using the following command
qiime feature-table filter-features \
--i-table table.qza \
--p-min-frequency 10 \
--o-filtered-table feature-frequency-filtered-table.qza
My initial data matrix had 2126 features across 190 samples and had a sparsity level of 0.97 (i.e. 97% of my matrix are zero values). After applying the above filter command it reduced to 1614 features across 190 samples with 0.96 sparsity.
I am currently debugging the annotation of my co-variates in my metadata file and playing around with running the model with fewer co-variates. I will keep you posted and do let me know if you find any issues with the sparsity level in my data matrix.
Thanks,
Ajay.