lateraldetect

Lateraldetect is a computational framework for identifying lateral gene transfer events in genomes. It combines signals from phylogenetic incongruence, nucleotide composition shifts, and synteny disruption to detect regions that may have originated outside the host lineage. Developed for microbial genomics, lateraldetect outputs a ranked list of candidate loci with accompanying confidence scores and explanatory features.

The workflow uses annotated genomes, gene families, and a reference species tree as input. It infers gene trees, measures incongruence with the reference, analyzes composition and codon usage, and assesses local gene order. Signals are integrated into a probabilistic score that ranks candidates and reports per-locus support metrics and potential donor clades.

Development and availability: Lateraldetect originated as an open-source project in the late 2010s, with ongoing community contributions. It is designed to interoperate with standard formats such as FASTA, GFF, and Newick, and runs on common operating systems. Documentation and example datasets accompany releases to support reproduction.

Applications and impact: The tool is used to study the role of lateral gene transfer in microbial evolution, including antibiotic resistance gene spread, metabolic pathway acquisition, and niche adaptation. Researchers employ it to generate hypotheses about transfer direction and to map the evolutionary history of transferred regions.

Limitations and considerations: Lateraldetect relies on the quality and sampling of input genomes. False positives can arise from convergent signals, gene loss, or paralogy; interpretation requires corroborating evidence. The method can be computationally intensive for large pangenomes and depends on appropriate model parameters.