Estimation of Gene Insertion/Deletion Rates with Missing Data.
Utkarsh J Dang, Alison M Devault, Tatum D Mortimer, Caitlin S Pepperell, Hendrik N Poinar, G Brian Golding
Author Information
Utkarsh J Dang: Departments of Biology and Mathematics and Statistics, McMaster University, Hamilton, Ontario L8S-4L8, Canada.
Alison M Devault: MYcroarray, Ann Arbor, Michigan 48105.
Tatum D Mortimer: Departments of Medicine and Medical Microbiology and Immunology, School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin 53705.
Caitlin S Pepperell: Departments of Medicine and Medical Microbiology and Immunology, School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin 53705.
Hendrik N Poinar: Department of Anthropology, McMaster University, Hamilton, Ontario L8S-4K1, Canada.
G Brian Golding: Department of Biology, McMaster University, Hamilton, Ontario L8S-4K1, Canada golding@mcmaster.ca.
Lateral gene transfer is an important mechanism for evolution among bacteria. Here, genome-wide gene insertion and deletion rates are modeled in a maximum-likelihood framework with the additional flexibility of modeling potential missing data. The performance of the models is illustrated using simulations and a data set on gene family phyletic patterns from Gardnerella vaginalis that includes an ancient taxon. A novel application involving pseudogenization/genome reduction magnitudes is also illustrated, using gene family data from Mycobacterium spp. Finally, an R package called indelmiss is available from the Comprehensive R Archive Network at https://cran.r-project.org/package=indelmiss, with support documentation and examples.
