LAIT: a local ancestry inference toolkit Public Deposited

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Creator
  • Lin, Jerome
    • Other Affiliation: Department of Human Genetics, University of Pittsburgh, Pittsburgh, USA
  • Chen, Wei
    • Other Affiliation: Department of Biostatistics, University of Pittsburgh, Pittsburgh, USA; Department of Human Genetics, University of Pittsburgh, Pittsburgh, USA; Division of Pulmonary Medicine, Allergy and Immunology, Department of Pediatrics, Children’s Hospital of Pittsburgh of UPMC, Pittsburgh, USA
  • Hu, Ming
    • Other Affiliation: Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, USA
  • Hui, Daniel
    • Other Affiliation: Department of Computer Science, University of Pittsburgh, Pittsburgh, USA
  • Duan, Qing
    • Affiliation: School of Medicine, Department of Genetics, Curriculum in Bioinformatics and Computational Biology, College of Arts and Sciences, Department of Computer Science, Department of Statistics and Operations Research
  • Li, Yun
    • Affiliation: School of Medicine, Department of Genetics, Gillings School of Global Public Health, Department of Biostatistics, College of Arts and Sciences, Department of Computer Science
  • Fang, Zhou
    • Other Affiliation: Affiliated with Department of Biostatistics, University of Pittsburgh, Pittsburgh, USA
Abstract
  • Abstract Background Inferring local ancestry in individuals of mixed ancestry has many applications, most notably in identifying disease-susceptible loci that vary among different ethnic groups. Many software packages are available for inferring local ancestry in admixed individuals. However, most of these existing software packages require specific formatted input files and generate output files in various types, yielding practical inconvenience. Results We developed a tool set, Local Ancestry Inference Toolkit (LAIT), which can convert standardized files into software-specific input file formats as well as standardize and summarize inference results for four popular local ancestry inference software: HAPMIX, LAMP, LAMP-LD, and ELAI. We tested LAIT using both simulated and real data sets and demonstrated that LAIT provides convenience to run multiple local ancestry inference software. In addition, we evaluated the performance of local ancestry software among different supported software packages, mainly focusing on inference accuracy and computational resources used. Conclusion We provided a toolkit to facilitate the use of local ancestry inference software, especially for users with limited bioinformatics background.
Date of publication
Identifier
  • doi:10.1186/s12863-017-0546-y
Resource type
  • Article
Rights statement
  • In Copyright
Rights holder
  • The Author(s).
Language
  • English
Bibliographic citation
  • BMC Genetics. 2017 Sep 06;18(1):83
Publisher
  • BioMed Central
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