Scalable Systems and Algorithms for Genomic Variant Analysis

With the cost of sequencing a human genome dropping below $1,000, population-scale sequencing has become feasible. In this dissertation, we describe the ADAM system for processing large genomic datasets using distributed computing. ADAM provides a decoupled stack-based architecture that can accommodate many data formats, deployment models, and data access patterns, and defines schemas that describe common genomic datatypes. To validate the ADAM architecture, we implemented an end-to-end variant calling pipeline using ADAM's APIs.