title: Detection of homologous recombination events in bacterial genomes.
abstract: We study the detection of mutations, sequencing errors, and homologous recombination events (HREs) in a set of closely related microbial genomes. We base the model on single nucleotide polymorphisms (SNPs) and break the genomes into blocks to handle the rearrangement problem. Then we apply a dynamic programming algorithm to model whether changes within each block are likely a result of mutations, sequencing errors, or HREs. Results from simulation experiments show that we can detect 31%-61% of HREs and the precision of our detection is about 48%-90% depending on the rates of mutation and missing data. The HREfinder software for predicting HREs in a set of whole genomes is available as open source (http://sourceforge.net/projects/hrefinder/).
authors.affiliation: Department of Computer Science, University of California Riverside, Riverside, California, United States of America.
authors.forename: Wei-Bung
authors.initials: WB
authors.lastname: Wang
authors.forename: Tao
authors.initials: T
authors.lastname: Jiang
authors.forename: Shea
authors.initials: S
authors.lastname: Gardner
mesh_terms: D000465:Algorithms; D016680:Genome, Bacterial; D023281:Genomics / Q000379:methods*; D059765:Homologous Recombination; D008957:Models, Genetic; D009154:Mutation; D020641:Polymorphism, Single Nucleotide; D012984:Software