pling

pling uses the Double Cut and Join Indel (DCJ-Indel) model to calculate distances between plasmids and cluster them for plasmid epidemiology.

Key Features:

• DCJ-Indel distance calculation: Calculates distances between plasmids as the minimum number of rearrangement events or indels needed to transform one plasmid into another, where plasmids are represented as a sequence of signed integers representing genes or aligned blocks.
• TE-aware network construction: Combines containment distances and DCJ-Indel distances to build a network that prevents promiscuous transposable elements from leading to over-clustering of unrelated plasmids.
• Plasmid clustering: Clusters plasmids based on calculated distances to enable epidemiological analysis.

Scientific Applications:

• Plasmid epidemiology: Tracks plasmids as vectors of antibiotic resistance by enabling evolutionary and epidemiological analysis that accounts for rapid structural changes in plasmid genomes.
• Hospital transmission analysis: Demonstrates superior performance and interpretability on hospital transmission datasets compared to other plasmid clustering tools.
• Plasmid relatedness assessment: Provides more meaningful distances between plasmids than approaches based on shared k-mer content, which can overestimate relatedness by ignoring rearrangements or underestimate by over-penalizing gene gain/loss.

Methodology:

pling represents plasmids as sequences of signed integers representing genes or aligned blocks, applies the DCJ-Indel model to compute rearrangement and indel distances, combines these with containment distances to account for transposable elements, and uses the resulting distances to cluster plasmids into a network.