Facilitating bootstrapped and rarefaction-based microbiome diversity analysis with q2-boots

Abstract

Background: We present q2-boots, a QIIME 2 plugin that facilitates bootstrapped and rarefaction-based microbiome diversity analysis. This plugin provides eight new actions that allow users to apply any of thirty different alpha diversity metrics and twenty-two beta diversity metrics to bootstrapped or rarefied feature tables, using a single QIIME 2 Pipeline command, or more granular QIIME 2 Action commands. Results: Given a feature table, an even sampling depth, and the number of iterations to perform (n), the command qiime boots core-metrics will resample the feature table n times and compute alpha and beta diversity metrics on each resampled table. The results will be integrated in summary data artifacts that are identical in structure and type to results that would be generated by applying diversity metrics to a single table. This enables all the same downstream analytic tools to be applied to these tables and ensures that all collected data is considered when computing microbiome diversity metrics. Conclusions: A challenge of this work was deciding how to integrate distance matrices that were computed on n resampled feature tables, as a simple average of pairwise distances (median or mean) does not account for the structure of distance matrices. q2-boots provides three options, and we show here that the results of these approaches are highly correlated. q2-boots is free and open source. Source code can be found at https://github.com/caporaso-lab/q2-boots; installation instructions and a tutorial can be found in the project’s documentation at https://q2-boots.readthedocs.io.