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Fisher Exact Test
Applies the Fisher Exact presence/absence test to a contingency table built based on the two selected pairwise categorical metadata values This test relies on the fisher.test function in the R stats package here
- Selecting OTUs or taxonomic groups ("OTU signature") that have a significant difference between two or more sample groups according to a presence/absence Fisher Exact test
The taxonomic level to aggregate the OTUs at. The OTUs will be grouped together (by summing the OTU values) at the selected taxonomic level before the analysis is applied.
Create comparative sample groups based on categorical variables uploaded in the metadata file.
Optionally create a categorical variable from a quantitative variable by using the Quantile Range feature on the Projects home page.
The two unique values for the selected Categorical Variable field that will be used to build a contingency table.
In the Fisher Exact test, this parameter controls what constitutes whether a taxonomic item is 'present' in a given sample.
By default, this is zero which means that a taxonomic item is present for a sample if it has a non-zero value for the sample. If this value was 10, this means that a taxonomic item must have a count of at least 10 for it to be considered present.
Only OTUs or taxonomic groups whose resultant p-value was less than this threshold will be displayed
Indicate whether the training set should remain the same every time a parameter is changed and the model is retrained.
Define the proportion of the data that should be randomly picked to form a training dataset.
You can set this value to be 1.0 if you don't plan on evaluating with a test dataset.
- Link back to boxplots
- Save Snapshot: Save the results to the experiment notebook
- Download: Downloads the results as a CSV file
- Share: Creates a shareable link that allows you to share the results with others