Development of computational techniques for genomic data analysis and visualisation in model and non-model organisms

Thanki, Anil (2019) Development of computational techniques for genomic data analysis and visualisation in model and non-model organisms. Doctoral thesis, University of East Anglia.

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Abstract

This thesis describes the work undertaken by the author between 2011 and 2018. With technological development, genome sequencing became affordable and accessible to the scientific communities. This led to the generation of an enormous amount of genomic data and bioinformatics tools to analyse and visualise these data. However, most of the public resources are designed for model organisms, and gold standard curated genomes. These tools are designed to run in a specifically configured environment as well as dependent on specific data formats. Chapter 1 of my thesis introduces the state of the field, the existing tools, their functionalities, and their limitations that prompted the software developments presented in the following chapters.

In chapter 2, I discuss the TGAC Browser, an open-source genome browser and wigExplorer, a BioJS plugin to visualise expression data. In chapter 3, I move towards finding gene families using GeneSeqToFamily, a Galaxy workflow based on the EnsemblCompara GeneTree pipeline. In chapter 4, I focus on a tool developed for visualisation of gene families - Aequatus, an open-source homology browser and ViCTreeView, a plugin developed as a part of the ViCTree project to visualise and explore phylogenetic trees.

In chapter 5, I discuss the availability and accessibility of these tools. All the tools and workflows I have developed are open-source, under a free licence, and are available in GitHub and/or the Galaxy ToolShed. I will also discuss the impact that these tools have made on various research projects. I also take this opportunity to discuss the possibilities of future developments of these tools.

Item Type:	Thesis (Doctoral)
Faculty \ School:	Faculty of Science > School of Biological Sciences
Depositing User:	Chris White
Date Deposited:	19 Oct 2022 13:29
Last Modified:	19 Oct 2022 13:29
URI:	https://ueaeprints.uea.ac.uk/id/eprint/89219
DOI:

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