We recommend running MaAsLin analyses independent of other comparative analyses. Once the parameters are set, click the Create button to start the MaAsLin2 workflow. Cosmos-Hub will process the data and return the results when the analysis is complete. Depending on the size of the dataset, the analysis may take a few minutes to 1+ hour.
Kepler-Taxa | HostAgnostic Functional | CHAMP-Taxa | CHAMP-Functional | |
---|---|---|---|---|
Metric | Relative Abundance | CPM | Relative Abundance | Cellular Abundance |
Taxonomic Level | Species | NA | Species | NA |
Min. Abundance* | 0.001 | 1000 | 0.001 | 0.01 |
Min. Prevalence** | 0.05 | 0.75 | 0.05 | 0.75 |
Q Threshold | 0.01 | 0.01 | 0.01 | 0.01 |
Normalization | NONE | TSS | NONE | NONE |
Transformation | LOG | LOG | LOG | LOG |
Analysis Method | LM | LM | LM | LM |
Multiple Correction | BH | BH | BH | BH |
Standardization | ✓ | ✓ | ✓ | ✓ |
N Heatmap | 100 | 100 | 100 | 100 |
*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.
Model | Data Type | Normalization | Transformation |
---|---|---|---|
LM | count and non-count | TSS,CLR, NONE | LOG, LOGIT, AST, NONE |
CPLM | count and non-count | TSS, TMM, CSS, NONE | NONE |
NEGBIN | count | TMM, CSS, NONE | NONE |
ZINB | count | TMM, CSS, NONE | NONE |