Predicting Mendelian Disease-Causing Non-Synonymous Single Nucleotide Variants in Exome Sequencing Studies

摘要: Exome sequencing is becoming a standard tool for mapping Mendelian disease-causing (or pathogenic) non-synonymous single nucleotide variants (nsSNVs). Minor allele frequency (MAF) filtering approach and functional prediction methods are commonly used to identify candidate pathogenic mutations in these studies. Combining multiple may increase accuracy prediction. Here, we propose use logit model combine compute an unbiased probability of rare variant being pathogenic. Also, the first time assess predictive power seven (including SIFT, PolyPhen2, CONDEL, logit) predicting nsSNVs from other variants, which reflects situation after MAF done exome-sequencing We found that combining all or some original outperforms examined, but unable discriminate between autosomal dominant recessive disease mutations. Finally, based on predictions model, estimate individual has around 5% carries ∼22 derived alleles at least, if made homozygous by consanguineous marriages lead diseases.