A framework to infer <i>de novo</i> exonic variants when parental genotypes are missing enhances association studies of autism.

ABSTRACT:

Motivation

Gene-damaging mutations are highly informative for studies seeking to discover genes underlying developmental disorders. Traditionally, these de novo variants are recognized by evaluating high-quality DNA sequence from affected offspring and parents. However, when parental sequence is unavailable, methods are required to infer de novo status and use this inference for association studies.

Results

We use data from autism spectrum disorder to illustrate and evaluate methods. Separating de novo from rare inherited variants is challenging because the latter are far more common. Using a classifier for unbalanced data and variants of known inheritance class, we build an inheritance model and then a de novo score for variants when parental dat

SUBMITTER: Moon H 

PROVIDER: S-EPMC12330658 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature