Facilitating bootstrapped and rarefaction-based microbiome diversity analysis with q2-boots
Isaiah Raspet, Elizabeth Gehret, Chloe Herman, Jeff Meilander, Andrew, Manley, Anthony Simard, Evan Bolyen, J. Gregory Caporaso

TL;DR
q2-boots is a QIIME 2 plugin that streamlines bootstrapped and rarefaction-based microbiome diversity analysis, enabling comprehensive and reproducible diversity metrics computation with multiple options for data integration.
Contribution
This work introduces a new QIIME 2 plugin that simplifies bootstrapped and rarefaction-based diversity analysis with multiple metrics and integration options.
Findings
Provides eight new actions for diversity analysis
Enables application of 30 alpha and 22 beta diversity metrics
Offers three methods for integrating distance matrices
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 of the same downstream analytic tools…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMetabolomics and Mass Spectrometry Studies · Gut microbiota and health · Bioinformatics and Genomic Networks
