Advances in Archaeological Geophysics: Case Studies from Historical Archaeology

This dissertation presents advanced methods in data processing, statistical analyses, integration, and visualization of archaeogeophysical data to increase the accuracy of archaeological remote sensing interpretation and predictions. Three case studies are presented from an experimental controlled archaeological test site and two nineteenth century historic military archaeology sites at Paint Rock, Texas and Alcatraz Island, California. I demonstrate the ability of the Geonics EM-63 time-domain electromagnetic-induction metal detector to detect and localize historical metal artifacts at an experimental site and Paint Rock. Moreover, point pattern analysis spatial autocorrelation statistics were used to detect statistically significant patterns that spatially compacted the amplitude response of the data to improve the localization of artifacts of archaeological significance. The archaeological data was used to determine the spatial and temporal extent of the military camp at Paint Rock and conforms well to the historic record. A virtual ground-truthing was conducted at Alcatraz Island, where the results of a quantitative attribute analysis of ground-penetrating radar data was tested against the georectification of historic maps in order to determine the location, extent, and integrity of historic military features without excavation. These studies increased the information content of archaeogeophysical data via feedback with statistics, quantitative attributes, controlled experiments, excavation, and georectification modeling in order to increase the predictive capabilities of the methods to answer the most questions with the least amount of costly excavations

Comprehensive Rare Variant Analysis via Whole-Genome Sequencing to Determine the Molecular Pathology of Inherited Retinal Disease

Inherited retinal disease is a common cause of visual impairment and represents a highly heterogeneous group of conditions. Here, we present findings from a cohort of 722 individuals with inherited retinal disease, who have had whole-genome sequencing (n = 605), whole-exome sequencing (n = 72), or both (n = 45) performed, as part of the NIHR-BioResource Rare Diseases research study. We identified pathogenic variants (single-nucleotide variants, indels, or structural variants) for 404/722 (56%) individuals. Whole-genome sequencing gives unprecedented power to detect three categories of pathogenic variants in particular: structural variants, variants in GC-rich regions, which have significantly improved coverage compared to whole-exome sequencing, and variants in non-coding regulatory regions. In addition to previously reported pathogenic regulatory variants, we have identified a previously unreported pathogenic intronic variant in $\textit{CHM}$ in two males with choroideremia. We have also identified 19 genes not previously known to be associated with inherited retinal disease, which harbor biallelic predicted protein-truncating variants in unsolved cases. Whole-genome sequencing is an increasingly important comprehensive method with which to investigate the genetic causes of inherited retinal disease.This work was supported by The National Institute for Health Research England (NIHR) for the NIHR BioResource – Rare Diseases project (grant number RG65966). The Moorfields Eye Hospital cohort of patients and clinical and imaging data were ascertained and collected with the support of grants from the National Institute for Health Research Biomedical Research Centre at Moorfields Eye Hospital, National Health Service Foundation Trust, and UCL Institute of Ophthalmology, Moorfields Eye Hospital Special Trustees, Moorfields Eye Charity, the Foundation Fighting Blindness (USA), and Retinitis Pigmentosa Fighting Blindness. M.M. is a recipient of an FFB Career Development Award. E.M. is supported by UCLH/UCL NIHR Biomedical Research Centre. F.L.R. and D.G. are supported by Cambridge NIHR Biomedical Research Centre