MicrobiomeAnalyst offers two types of data filters: low-count filter and low-variance filter
- Low count filter - features with very small counts in very few samples are likely due to sequencing errors or low-level contaminations. You need to first specify a minimum count (default 4). A 20% prevalence filter means at least 20% of its values should contain at least 4 counts. You can also filter based on their mean or median values.
- Low variance filter - features that are close to constant throughout the experiment conditions are unlikely to be associated with the conditions under study. Their variances can be measured using inter-quantile range (IQR), standard deviation or coefficient of variation (CV).
Note that users can disable any data filter by dragging the slider to the left end (value: 0) .