Prokounter

Prokounter models and corrects spurious taxon generation in 16S rRNA marker gene surveys to enable accurate differential richness inference in microbial communities.

Key Features:

• Modeling of spurious taxa generation: Models systematic patterns of spurious sub-genus taxa generation arising from clustering of 16S sequencing reads as a function of genus abundance.
• False taxa controls: Derives robust controls for false taxa accumulation to correct inflated observed taxon counts.
• Differential richness inference: Enables accurate differential richness inference across sample groups and specific taxa collections.
• Regression integration: Facilitates the use of classical regression approaches for testing richness differences.
• Bias mitigation: Mitigates biases introduced by false species discoveries that confound traditional richness methods.
• Evidence-based design: Is grounded in experimental evidence, theory-guided exploratory data analyses, and existing literature.

Scientific Applications:

• Microbiome diversity analysis in 16S rRNA marker gene surveys: Provides corrected richness estimates for analyses of microbial community diversity measured by 16S rRNA sequencing.
• Comparative richness testing: Supports differential richness testing between sample groups and across defined taxa collections.
• Associations with health and environment: Enables more reliable analyses linking changes in microbiome diversity to individual and environmental health outcomes.

Methodology:

Models systematic patterns of spurious sub-genus taxa generation as a function of genus abundance, derives controls for false taxa accumulation, and applies classical regression approaches for differential richness inference.