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AUDACITY: A comprehensive approach for the detection and classification of Runs of Homozygosity in medical and population genomics

Runs of Homozygosity (RoHs) are popular among geneticists as the footprint of demographic processes, evolutionary forces and inbreeding in shaping our genome, and are known to confer risk of Mendelian and complex diseases. Notwithstanding growing interest in their study, there is unmet need for reli...

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Detalles Bibliográficos
Autores principales: Magi, Alberto, Giangregorio, Tania, Semeraro, Roberto, Carangelo, Giulia, Palombo, Flavia, Romeo, Giovanni, Seri, Marco, Pippucci, Tommaso
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7394861/
https://www.ncbi.nlm.nih.gov/pubmed/32774790
http://dx.doi.org/10.1016/j.csbj.2020.07.003
Descripción
Sumario:Runs of Homozygosity (RoHs) are popular among geneticists as the footprint of demographic processes, evolutionary forces and inbreeding in shaping our genome, and are known to confer risk of Mendelian and complex diseases. Notwithstanding growing interest in their study, there is unmet need for reliable and rapid methods for genomic analyses in large data sets. AUDACITY is a tool integrating novel RoH detection algorithm and autozygosity prediction score for prioritization of mutation-surrounding regions. It processes data in VCF file format, and outperforms existing methods in identifying RoHs of any size. Simulations and analysis of real exomes/genomes show its potential to foster future RoH studies in medical and population genomics.