Machine Learning Models for Genetic Risk Assessment of Infants with Non-syndromic Orofacial Cleft.

ABSTRACT: The isolated type of orofacial cleft, termed non-syndromic cleft lip with or without cleft palate (NSCL/P), is the second most common birth defect in China, with Asians having the highest incidence in the world. NSCL/P involves multiple genes and complex interactions between genetic and environmental factors, imposing difficulty for the genetic assessment of the unborn fetus carrying multiple NSCL/P-susceptible variants. Although genome-wide association studies (GWAS) have uncovered dozens of single nucleotide polymorphism (SNP) loci in different ethnic populations, the genetic diagnostic effectiveness of these SNPs requires further experimental validation in Chinese populations before a diagnostic panel or a predictive model covering multiple SNPs can be built. In this study, we collected

SUBMITTER: Zhang SJ 

PROVIDER: S-EPMC6364041 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature