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Leveraging Identity-by-Descent for Accurate Genotype Inference in Family Sequencing Data


To identify disease variants that occur less frequently in population, sequencing families in which multiple individuals are affected is more powerful due to the enrichment of causal variants. An important step in such studies is to infer individual genotypes from sequencing data. Existing methods do not utilize full familial transmission information and therefore result in reduced accuracy of inferred genotypes. In this study we describe a new method that infers shared genetic materials among family members and then incorporate the shared genomic information in a novel algorithm that can accurately infer genotypes. Our method is particularly advantageous when inferring low frequency variants with fewer sequence data, making it effective in analyzing genome-wide sequence data. We implemented the algorithm in a computationally efficient tool to facilitate cost-effective sequencing in families for identifying disease genetic variants.


Vyšlo v časopise: Leveraging Identity-by-Descent for Accurate Genotype Inference in Family Sequencing Data. PLoS Genet 11(6): e32767. doi:10.1371/journal.pgen.1005271
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pgen.1005271

Souhrn

To identify disease variants that occur less frequently in population, sequencing families in which multiple individuals are affected is more powerful due to the enrichment of causal variants. An important step in such studies is to infer individual genotypes from sequencing data. Existing methods do not utilize full familial transmission information and therefore result in reduced accuracy of inferred genotypes. In this study we describe a new method that infers shared genetic materials among family members and then incorporate the shared genomic information in a novel algorithm that can accurately infer genotypes. Our method is particularly advantageous when inferring low frequency variants with fewer sequence data, making it effective in analyzing genome-wide sequence data. We implemented the algorithm in a computationally efficient tool to facilitate cost-effective sequencing in families for identifying disease genetic variants.


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Genetika Reprodukčná medicína

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PLOS Genetics


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