Why should I use the data filtering option?

The purpose of data filtering is to allow users to remove low quality and/or uninformative features to improve downstream statisitcal analysis. MicrobiomeAnalyst contains three data filtering procedures:

  1. Minimal data filtering (applied to all analysis) - the procedure will remove features containing all zeros, or appearing in only one sample. These extremely rare features should be removed from consideration;
  2. Low abundance features - they may be due to sequencing errors or low-level contaminations;
  3. Low variance features - they are unlikely to be associated with the conditions under study;

Note, the last two options are not used for within-sample (alpha diversity) profiling, but are strongly recommended for comparative analysis.