Kepler-Taxa | HostAgnostic Functional | CHAMP-Taxa | CHAMP-Functional | |
---|---|---|---|---|
Metric | Relative Abundance | CPM | Relative Abundance | Cellular Abundance |
Taxonomic Level | Species | NA | Species | NA |
Fixed Effect | Metadata of Interest | Metadata of Interest | Metadata of Interest | Metadata of Interest |
Random Effect | OptionalVariables | OptionalVariables | OptionalVariables | OptionalVariables |
Longitudinal and Complex Association Formula (Optional) | See page | See page | See page | See page |
Min. Abundance* | 0 | 1 | 0 | 0.1 |
Min. Prevalence** | 0 | 0.10 | 0 | 0.25 |
Zero Threshold | 0 | 0 | 0 | 0 |
Minimum Variance | 0 | 0 | 0 | 0 |
Q Threshold | 0.25 | 0.25 | 0.25 | 0.01 |
Normalization | TSS | TSS | TSS | NONE |
Transformation | LOG | LOG | LOG | LOG |
Multiple Correction | BH | BH | BH | BH |
Standardization | ||||
Augmentation | ||||
Median Comparison Abundance Compositional Correction | ||||
Median Comparison Abundance Threshold | 0 | 0 | 0 | 0 |
Median Comparison Prevalence Compositional Correction | 0 | 0 | 0 | 0 |
Subtract Median | FALSE | FALSE | FALSE | FALSE |
Maximum Number of Associations to Plot | 50 | 50 | 50 | 50 |
Number of Features in Summary Plot | 25 | 25 | 25 | 25 |
*A single hit can always be a sequencing error, contamination error, or other noise variables etc. Implementing a minimum abundance with minimum prevalence cutoff can ensure more accurate multi-variate association analysis data. **Samples are far richer in functional hits than in taxonomic hits. Non-prevalent functions can sharply increase computational time and may include false positives, which is why more stringent cutoffs are recommended.