Project Summary Birth defects cause significant health and economic burdens to families and societies globally. In recent years, advances in biotechnologies, such as next-generation sequencing, have helped to identify many disease- causing genes for birth defects and childhood cancers. Although the identified genes only explain a small proportion of the cases, these advancements demonstrate the promise of identifying more birth defect-causing genes from the analysis of sequencing data through powerful statistical methods. The NIH Common Fund established the Gabriella Miller Kids First Pediatric Research Program (Kids First) to “develop a pediatric research data resource populated by genome sequence and phenotype data that will be of high value for the communities of investigators who study the genetics of childhood cancers and/or structural birth defects.” The ultimate goal of this project is to develop, implement, and apply novel statistical methods to improve the power of identifying genes causing birth defects across a number of conditions using data from the Kids First Data Resource Center and to make the developed tools available to the scientific community. This will be accomplished through three specific aims. First, we will develop a statistical framework that can simultaneously consider different disease models – including both de novo mutations and rare inherited variants – to more effectively identify disease-causing genes from whole exome sequencing data. Second, we will develop statistical methods to quantify the degree of shared de novo mutation contributions to different birth defects and also methods that can leverage this shared genetics to identify disease-causing genes. Third, after evaluating the performance of our developed methods, we will implement these methods and apply them to the birth defect cohorts currently available at the Kids First Data Resource Center as well as other data sets that will be added in the future. We will also disseminate the software to the scientific community. In accomplishing our aims, we will contribute new statistical tools to analyze birth defects cohorts as well as make new biological discoveries of genes and pathways for different birth defects.