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Title: Bioinformatic investigations into the genetic architecture of renal disorders
Author: Cheshire, Christopher
ISNI:       0000 0004 8507 688X
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2019
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Modern genomic analysis has a significant bioinformatic component due to the high volume of complex data that is involved. During investigations into the genetic components of two renal diseases, we developed two software tools. Genome-Wide Association Studies (GWAS) datasets may be genotyped on different microarrays and subject to different annotation, leading to a mosaic case-control cohort that has inherent errors, primarily due to strand mismatching. Our software REMEDY seeks to detect and correct strand designation of input datasets, as well as filtering for common sources of noise such as structural and multi-allelic variants. We performed a GWAS on a large cohort of Steroid-sensitive nephrotic syndrome samples; the mosaic input datasets were pre-processed with REMEDY prior to merging and analysis. Our results show that REMEDY significantly reduced noise in GWAS output results. REMEDY outperforms existing software as it has significantly more features available such as auto-strand designation detection, comprehensive variant filtering and high-speed variant matching to dbSNP. The second tool supported the analysis of a newly characterised rare renal disorder: Polycystic kidney disease with hyperinsulinemic hypoglycemia (HIPKD). Identification of the underlying genetic cause led to the hypothesis that a change in chromatin looping at a specific locus affected the aetiology of the disease. We developed LOOPER, a software suite capable of predicting chromatin loops from ChIP-Seq data to explore the possible conformations of chromatin architecture in the HIPKD genomic region. LOOPER predicted several interesting functional and structural loops that supported our hypothesis. We then extended LOOPER to visualise ChIA-PET and ChIP-Seq data as a force-directed graph to show experimental structural and functional chromatin interactions. Next, we re-analysed the HIPKD region with LOOPER to show experimentally validated chromatin interactions. We first confirmed our original predicted loops and subsequently discovered that the local genomic region has many more chromatin features than first thought.
Supervisor: Stanescu, H. ; Kleta, R. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available