This study will significantly increase our understanding of pediatric cardiomyopathy by defining the prevalence of mutations in genes known to cause cardiomyopathy as well as identifying novel disease-causing genes in the pediatric population. Genetic association tests will identify variants that modify disease. Novel bioinformatics and systems biology applications for interpretation of exome level genetic information will contribute fundamental knowledge and technical innovation to the translation of genomic data to clinical utility. These aims will provide critical genetic architecture data, identify variants with large effects, and enable genotype-phenotype correlations necessary for advancing management and therapy.