bioconductor-dspikein
Estimating Absolute Abundance from Microbial Spike-in Controls
Estimating Absolute Abundance from Microbial Spike-in Controls
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Provides a reproducible and modular workflow for absolute microbial quantification using spike-in controls. Supports both single spike-in taxa and synthetic microbial communities with user-defined spike-in volumes and genome copy numbers. Compatible with 'phyloseq' and 'TreeSummarizedExperiment' (TSE) data structures. The package implements methods for spike-in validation, preprocessing, scaling factor estimation, absolute abundance conversion, bias correction, and normalization. Facilitates downstream statistical analyses with 'DESeq2', 'edgeR', and other Bioconductor-compatible methods. Visualization tools are provided via 'ggplot2', 'ggtree', and related packages. Includes detailed vignettes, case studies, and function-level documentation to guide users through experimental design, quantification, and interpretation.
Summary
Estimating Absolute Abundance from Microbial Spike-in Controls
Last Updated
Mar 1, 2026 at 18:30
License
MIT + file LICENSE
Supported Platforms