Mary K Kuhner

Summary

Affiliation: University of Washington
Country: USA

Publications

  1. ncbi Comparing likelihood and Bayesian coalescent estimation of population parameters
    Mary K Kuhner
    Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
    Genetics 175:155-65. 2007
  2. ncbi Robustness of coalescent estimators to between-lineage mutation rate variation
    Mary K Kuhner
    Department of Genome Sciences, University of Washington, Seattle, WA, USA
    Mol Biol Evol 23:2355-60. 2006
  3. ncbi The limits of fine-scale mapping
    Lucian P Smith
    Department of Genome Sciences, University of Washington, Seattle, WA 98195 5065, USA
    Genet Epidemiol 33:344-56. 2009
  4. ncbi LAMARC 2.0: maximum likelihood and Bayesian estimation of population parameters
    Mary K Kuhner
    Department of Genome Sciences Box 357730 University of Washington Seattle, 98195 7730, USA
    Bioinformatics 22:768-70. 2006
  5. ncbi Coalescent genealogy samplers: windows into population history
    Mary K Kuhner
    Department of Genome Sciences, University of Washington, Seattle, WA 98195 5065, USA
    Trends Ecol Evol 24:86-93. 2009

Collaborators

Detail Information

Publications5

  1. ncbi Comparing likelihood and Bayesian coalescent estimation of population parameters
    Mary K Kuhner
    Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
    Genetics 175:155-65. 2007
    ..However, the Bayesian approach rejected the generative parameter values significantly less often than the likelihood approach, both in cases where the level of rejection was normal and in cases where it was too high...
  2. ncbi Robustness of coalescent estimators to between-lineage mutation rate variation
    Mary K Kuhner
    Department of Genome Sciences, University of Washington, Seattle, WA, USA
    Mol Biol Evol 23:2355-60. 2006
    ..Both estimators are robust to modest rate variation; however, their use should be coupled with a statistical test to rule out extreme rate variation as the resulting CIs may not be reliable...
  3. ncbi The limits of fine-scale mapping
    Lucian P Smith
    Department of Genome Sciences, University of Washington, Seattle, WA 98195 5065, USA
    Genet Epidemiol 33:344-56. 2009
    ..If haplotypes are unknown due to incomplete penetrance, much information is lost, with more information lost the less indicative phenotype is of the underlying genotype...
  4. ncbi LAMARC 2.0: maximum likelihood and Bayesian estimation of population parameters
    Mary K Kuhner
    Department of Genome Sciences Box 357730 University of Washington Seattle, 98195 7730, USA
    Bioinformatics 22:768-70. 2006
    ..It is available as portable source code and executables for all three major platforms. AVAILABILITY: LAMARC 2.0 is freely available at http://evolution.gs.washington.edu/lamarc..
  5. ncbi Coalescent genealogy samplers: windows into population history
    Mary K Kuhner
    Department of Genome Sciences, University of Washington, Seattle, WA 98195 5065, USA
    Trends Ecol Evol 24:86-93. 2009
    ..This review summarizes available genealogy-sampler software, including data requirements and limitations on the use of each program...