Whole genome shotgun assembly in theory and practice

The subject of this dissertation is the development of novel analytical and algorithmic approaches to the fragment assembly problem in the context of the Whole Genome Shotgun (WGS) DNA sequencing strategy. A collection of analyses and methods centered on the computational reconstruction of genomic DNA sequence from randomly sampled genome fragments, with particular focus on applications to large, polymorphic, and inhomogeneous datasets are presented. Several novel pre-assembly WGS data analyses are described including assessment of genome size, sequence uniformity, and repetitive element content with particular emphasis on the establishment of standardized quality assurance metrics for large WGS sequencing projects. A theoretical framework for understanding the statistical properties of WGS assemblies in the presence of paired-end sequence data is discussed and the algorithmic sub-problems of quality-based sequence trimming, global pairwise alignment detection, and consensus sequence generation are treated. Finally, as a novel application of these analyses and methods, the results of a collaboration to produce the first WGS sequence reconstruction of a community sample from a natural environment are presented.