phylofunc

phylofunc incorporates microbiome phylogeny into metaproteomic functional distance calculations, enabling more informative analyses of microbial community functional profiles.

Key Features:

• Phylogeny-informed functional beta-diversity: Utilizes branch lengths to weigh between-sample functional distances for each taxon, rather than differences in taxonomic abundance as in weighted UniFrac.
• Functional compensatory effect detection: Captures functional compensatory effects between phylogenetically related taxa that traditional approaches miss.
• Distance matrix generation: Calculates functional beta-diversity distances between a pair of samples or generates a distance matrix for all samples within a dataset.
• Python package implementation: Provided as an open-source Python package for efficient computation.

Scientific Applications:

• Dietary intervention studies: Applied to mouse gut microbiome datasets with synthetic microbiome inoculation under different dietary conditions.
• Drug response analysis: Demonstrated higher sensitivity in detecting microbiome responses to paracetamol compared to traditional distance methods using complex human gut microbiome datasets treated with five different drugs.
• Ecological metric development: Serves as a novel ecological metric for exploring functional dissimilarities between microbial communities in metaproteomic data analysis.

Methodology:

Leverages the phylogenetic framework of weighted UniFrac distance, utilizing branch lengths to weigh between-sample functional distances for each taxon. PCoA and machine learning-based classification algorithms were used to evaluate performance against traditional distance methods.