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MBRarefy: data-adaptive multi-bin rarefying for alpha div...
[Submitted on 19 Jun 2026] · 2026-06-23 · via stat updates on arXiv.org

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Abstract:Summary: This paper presents MBRarefy, an R package that provides a reproducible workflow for alpha diversity analysis under confounding from heterogeneous library sizes. Building on the multi-bin rarefying approach in Li et al (2024), MBRarefy supports alpha diversity association analysis with repeated rarefying, bin-wise testing, and cross-bin meta-analysis. A key new feature is automated, data-adaptive selection of library size bin thresholds via a genetic algorithm (GA), which replaces ad hoc cutpoints with an objective optimization procedure based on the rarefying-derived profiles. The package also supports routine data-management tasks, including file-based sample-wise processing and standardized output generation, enabling users to execute the full analysis pipeline from raw count files to combined inferential results.
Availability and implementation: The R package MBRarefy is freely available on GitHub at this https URL.

Submission history

From: Mo Li [view email]
[v1] Fri, 19 Jun 2026 00:23:32 UTC (1,385 KB)