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Genomic data analysis: populations, patients and pipelines

Genomic data analysis: populations, patients and pipelines
Genomic data analysis: populations, patients and pipelines
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
Pengelly, Reuben
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Pengelly, Reuben
af97c0c1-b568-415c-9f59-1823b65be76d
Ennis, Sarah
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Collins, Andrew
7daa83eb-0b21-43b2-af1a-e38fb36e2a64
Gibson, Jane
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Pengelly, Reuben (2015) Genomic data analysis: populations, patients and pipelines. University of Southampton, Faculty of Medicine, Doctoral Thesis, 216pp.

Record type: Thesis (Doctoral)

Abstract

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

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Published date: October 2015
Organisations: University of Southampton, Human Development & Health

Identifiers

Local EPrints ID: 397102
URI: http://eprints.soton.ac.uk/id/eprint/397102
PURE UUID: 25216740-e62e-4c73-8698-1eb7075c0a8b
ORCID for Reuben Pengelly: ORCID iD orcid.org/0000-0001-7022-645X
ORCID for Sarah Ennis: ORCID iD orcid.org/0000-0003-2648-0869
ORCID for Andrew Collins: ORCID iD orcid.org/0000-0001-7108-0771
ORCID for Jane Gibson: ORCID iD orcid.org/0000-0002-0973-8285

Catalogue record

Date deposited: 19 Jul 2016 13:04
Last modified: 15 Mar 2024 03:48

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Contributors

Author: Reuben Pengelly ORCID iD
Thesis advisor: Sarah Ennis ORCID iD
Thesis advisor: Andrew Collins ORCID iD
Thesis advisor: Jane Gibson ORCID iD

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