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PCAdmix: A PCA based software package for calling local ancestry in admixed populations


Stanford Reference:

11-395


Abstract


Stanford researchers have developed PCAdmix, which is a software package designed to infer local ancestry along the genome of an admixed individual using phased or unphased genotyping data. This method is flexible allowing for two or more ancestral source populations and allows for fine control via numerous user-specified options including time since admixture, data thinning, window size, and calling threshold. The resulting output is easily interpreted and includes assessments of calling confidence.
High confidence assessment of local ancestry along the genome in admixed individuals is critical for applications such as basic ancestry inference and admixture mapping of traits for disease variants.

Stage of Research:
- Reduced to practice - PCAdmix 1.0 has been compiled for Windows, MACOSX and Linux
- Continued research to improve existing features and add new features



Applications


  • Basic ancestry inference
  • Admixture mapping of traits including disease variants
  • Population structure correction in genome-wide association studies (GWAS)
  • Population demographic inference for admixed populations
  • Inheritance inference in admixed populations

Advantages


  • Analyzes complicated admixture involving two or more ancestral sources. Previous methods tend to struggle with more than two sources
  • Uses common input data type - PCAdmix can be used with raw genotypes or phased haplotypes for better assignment
  • It is fast and flexible allowing user-based control of most relevant features
  • Results are easy to interpret

Publications


  • Brisbin, A. (2010). "Linkage Analysis for Categorical Traits and Ancestry Assignment in Admixed Individuals." Doctoral Dissertation, Cornell University, Ithaca, NY.




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Date Released

 4/23/2013
 

Licensing Contact


Ximena Ares, Licensing Associate
650-724-0960 (Direct)
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Related Keywords


software: bioinformatics   genome-wide association studies (GWAS)   genomic analysis   genomics: bioinformatic   genomics: genotype   genomics: polymorphism   ancestry analysis   11-395   
 

   

  

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