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Significance Associated with Phenotype (SAP) Score Aids in Variant Prioritization for Exome Sequencing Analysis

外显子组测序 表型 外显子组 计算生物学 遗传学 生物信息学 生物 基因
作者
Brian Lee,Lily Nasanovsky,Li Shen,Dennis T. Maglinte,Yachen Pan,Xiaowu Gai,Ryan J. Schmidt,Gordana Raca,Jaclyn A. Biegel,Megan Roytman,Paul An,Carol Saunders,Emily Farrow,Soheil Shams,Jianling Ji
出处
期刊:The Journal of Molecular Diagnostics [Elsevier]
标识
DOI:10.1016/j.jmoldx.2024.01.009
摘要

Several in silico annotation-based methods have been developed to prioritize variants in exome sequencing analysis. This study introduces a novel metric, the Significance Associated with Phenotypes (SAP) score, which generates a statistical score by comparing an individual's observed phenotypes against existing gene-phenotype associations. To evaluate the SAP score, a retrospective analysis was performed on 219 exomes. Among them, 82 family-based and 35 singleton exomes had at least one disease-causing variant explaining the patient’s clinical features. SAP scores were calculated, and the rank of the disease-causing variant was compared to a known method, Exomiser. Using the SAP score, the known causative variant was ranked in the top 10 retained variants for 94% (77/82) of the family-based exomes and in the first place for 73% of these cases. For singleton exomes, the SAP score analysis ranked the known pathogenic variants within the top 10 for 80% (28/35) of the cases. The SAP score, which is independent of detected variants, demonstrates comparable performance to Exomiser, which considers both phenotype and variant-level evidence simultaneously. Among 102 cases with negative results or variants of uncertain significance, SAP score analysis revealed two cases with a potential new diagnosis based on rank. The SAP score, a phenotypic quantitative metric, can be utilized in conjunction with standard variant filtration and annotation to enhance variant prioritization in exome analysis.
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