This thesis describes the conception, design, and development of novel computational tools, theoretical models, and experimental techniques applied to the dissection of molecular factors underlying phenotypic variation. The first part of my work is focused on finding rare genetic variants in pooled DNA samples, leading to the development of a novel set of algorithms, SNPseeker and SPLINTER, applied to next-generation sequencing data. The second part of my work describes the creation of a reporter system for DNA methylation for the purpose of dissecting the genetic contribution of tissue-specific patterns of DNA methylation across the genome. Finally the last part of my work is focused on understanding the basis of stochastic variation in gene expression with a focus on modeling and dissecting the relationship between single-cell protein variance and mean at a genome-wide scale
