NetFrac

NetFrac calculates distances and indices to quantify community dissimilarities within sequence similarity networks (SSNs) for analysis of reticulate evolutionary processes such as horizontal gene transfer, mosaic genomes, and microbiota-associated antibiotic resistance.

Key Features:

• Shortest Path-Based Distances: Introduces five shortest path-based distances—Spp, Spep, Spelp, Spinp, and NetUniFrac—that extend shortest-path concepts from phylogenetic trees to SSNs as network analogs of UniFrac.
• Transfer Index: Provides a Transfer index that estimates the rate and direction of gene transfers or species dispersal between phylogenetic or ecological communities, informing analyses of horizontal gene transfer and recombination.
• Efficiency in Computation: Computes NetUniFrac and the Transfer index in linear time relative to the number of network edges, enabling application to large molecular datasets.
• Adapted Measures: Incorporates adapted measures from the literature, including UniFrac and Motifs, to complement the novel network distances.

Scientific Applications:

• Identification of Horizontal Gene Transfer Events: Uses shortest path-based distances and the Transfer index to detect and characterize gene transfer events within microbial communities.
• Recovery of Mosaic Genes and Genomes: Aids reconstruction of mosaic genes and genomes by analyzing topology and community structure in SSNs.
• Study of Holobionts: Supports analysis of microbiota and antibiotic resistance gene similarity networks to investigate holobiont composition and dynamics.
• Reticulate Evolution Analysis: Applies to evolutionary biology, ecology, and bioinformatics studies focused on reticulate evolutionary processes and community dissimilarity.

Methodology:

Represents sequence similarity networks as igraph objects (nodes and edges), applies graph-theoretical approaches to compute distances and indices, and is implemented in R and C.