Identification of Transdiagnostic Childhood Externalizing Pathology Within an Electronic Medical Records Database and Application to the Analysis of Rare Copy Number Variation.

Externalizing traits and behaviors are broadly defined by impairments in self-regulation and impulse control that typically begin in childhood and adolescence. Externalizing behaviors, traits, and symptoms span a range of traditional psychiatric diagnostic categories. In this study, we sought to generate an algorithm that could reliably identify transdiagnostic childhood-onset externalizing cases and controls within a university hospital electronic health record (EHR) database.

Mapping the landscape of lineage-specific dynamic regulation of gene expression using single-cell transcriptomics and application to genetics of complex disease.

Single-cell transcriptome data can provide insights into how genetic variation influences biological processes involved in human biology and disease. However, the identification of gene-level associations in distinct cell types faces several challenges, including the limited reference resource from population scale studies, data sparsity in single-cell RNA sequencing, and the complex cell state pattern of expression within individual cell types. Here we develop genetic models of cell type specific and cell state adjusted gene expression in mid-brain neurons in the process of specializing from induced pluripotent stem cells.

Evaluating the impact of modeling choices on the performance of integrated genetic and clinical models.

Purpose: The value of genetic information for improving the performance of clinical risk prediction models has yielded variable conclusions. Many methodological decisions have the potential to contribute to differential results. We performed multiple modeling experiments integrating clinical and demographic data from electronic health records (EHR) with genetic data to understand which decisions may affect performance.