Affiliation:
1. Computational Biology Division, Department of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine University of Cape Town Health Sciences Campus Anzio Rd, Observatory, 7925, South Africa
Abstract
Abstract
Several thousand genomes have been completed with millions of variants identified in the human deoxyribonucleic acid sequences. These genomic variations, especially those introduced by admixture, significantly contribute to a remarkable phenotypic variability with medical and/or evolutionary implications. Elucidating local ancestry estimates is necessary for a better understanding of genomic variation patterns throughout modern human evolution and adaptive processes, and consequences in human heredity and health. However, existing local ancestry deconvolution tools are accessible as individual scripts, each requiring input and producing output in its own complex format. This limits the user’s ability to retrieve local ancestry estimates. We introduce a unified framework for multi-way local ancestry inference, FRANC, integrating eight existing state-of-the-art local ancestry deconvolution tools. FRANC is an adaptable, expandable and portable tool that manipulates tool-specific inputs, deconvolutes ancestry and standardizes tool-specific results. To facilitate both medical and population genetics studies, FRANC requires convenient and easy to manipulate input files and allows users to choose output formats to ease their use in further potential local ancestry deconvolution applications.
Funder
National Institutes of Health Common Fund—H3ABioNet
Publisher
Oxford University Press (OUP)
Subject
Molecular Biology,Information Systems
Cited by
3 articles.
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