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Title: Genomic data analysis : populations, patients & pipelines
Author: Pengelly, Reuben
ISNI:       0000 0004 5922 3313
Awarding Body: University of Southampton
Current Institution: University of Southampton
Date of Award: 2015
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Methods for the ascertainment of genotype data have become more cost efficient by orders of magnitude with the use of high-density genotyping arrays and the advent of next generation sequencing (NGS). The resulting deluge of data has required ever advancing analytical approaches in order for the maximal information to be gleaned from these extensive data. In this work, many application of NGS to clinical research are discussed. This includes the application of targeted gene sequencing to a cohort of 83 patients with chronic kidney disease, whole-exome investigations of eight families with cleft lip/palate phenotypes, as well as five cases where analytical lessons can be learned from exome sequenced cases harbouring pathogenic variants refractory to identification. Additionally, a novel QC tool for the unambiguous tracking of samples undergoing exome sequencing is presented. Furthermore, work is presented investigating the linkage disequilibrium (LD) patterns in populations applying the Malecot-Morton model. We demonstrate that array genotyping is insufficient for the accurate determination of ne LD patterns in the human genome, with whole-genome sequencing providing more representative LD maps. Finally, we apply similar methods to Gallus gallus, generating the highest resolution maps of LD presented to date, showing that the patterns are highly discordant between commercial lines, and define features associated with recombination. Overall, we highlight the diversity of ways in which genetic data can be utilised effectively in the age of genomic `big data', and present tools which may be of benefit to other researchers utilising these technologies.
Supervisor: Ennis, Sarah ; Collins, Andrew ; Gibson, Jane Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available