Abstract
BackgroundInferring 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.ResultsWe 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.ConclusionWe provided a toolkit to facilitate the use of local ancestry inference software, especially for users with limited bioinformatics background.
Highlights
Inferring local ancestry in individuals of mixed ancestry has many applications, most notably in identifying disease-susceptible loci that vary among different ethnic groups
Genetic studies of admixed populations such as Latinos and African Americans have been successful in identifying disease-susceptible loci, which can be difficult to detect by other methods such as genome-wide association studies (GWAS)
FASTQ and SAM formats are commonly used for sequencing analysis and PLINK format is used for GWAS
Summary
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. We evaluated the performance of local ancestry software among different supported software packages, mainly focusing on inference accuracy and computational resources used
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