Differentially Abundant Analysis Results with Annotation — daa_annotated_results

This is a result dataset after processing 'kegg_abundance' through the 'pathway_daa' with the LinDA method and further annotation with 'pathway_annotation'.

Usage

daa_annotated_results_df

Format

A data frame with 10 variables:

adj_method: Method used for adjusting p-values.
feature: Feature being tested.
group1: One group in the comparison.
group2: The other group in the comparison.
method: Statistical test used.
p_adjust: Adjusted p-value.
p_values: P-values from the statistical test.
pathway_class: Class of the pathway.
pathway_description: Description of the pathway.
pathway_map: Map of the pathway.
pathway_name: Name of the pathway.

Source

From ggpicrust2 package demonstration.

References

Douglas GM, Maffei VJ, Zaneveld J, Yurgel SN, Brown JR, Taylor CM, Huttenhower C, Langille MGI. PICRUSt2 for prediction of metagenome functions. Nat Biotechnol. 2020.