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Computational approaches for determination of transcriptomic and epigenomic states
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Lipecki, Julia (2020) Computational approaches for determination of transcriptomic and epigenomic states. PhD thesis, University of Warwick.
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Official URL: http://webcat.warwick.ac.uk/record=b3467866~S15
Abstract
Over the last half century, major advances in molecular biology methods and technologies have inspired significant progress in research across all branches of life sciences. In particular, transcriptomic and epigenomic profiling have allowed for detailed studies of gene regulation, as data from both techniques reflect a multitude of biological processes and responses. As such, there exists a need for computational approaches that can recognise the associated biological states with confidence, which is the main focus of this thesis.
First, chapter 3 presents a novel tool - JACC (Julia’s Algorithm for Cell Classification) the Ripper - for cell clustering of scRNA-Seq data, which takes advantage of the intrinsic multimodality of gene expression profiles within such datasets to split the cells into their corresponding cell types. This tool is among the first of its kind, offering multiple advantages over standard clustering work-flows, including its ability to identify rare cell populations and generation of a report clearly documenting the reasons behind each splitting decision thereby providing evidence and transparency to the user. As such, JACC can be used in any scRNA-Seq research setting.
Second, chapter 4 introduces a novel method - ESPAM (Endometrial Secretory Phase Assignment Model) - for the assessment of secretory phase progress of endometrial biopsy samples based on a specifically designed RT-qPCR gene expression measurement assay. The model combines data binning with probability density estimates to obtain timing predictions of samples, alongside also providing a measure for tissue asynchrony which flags up any samples with unusually noisy gene measurements. ESPAM can be used in both clinical and research environments, as the model can facilitate any endometrial analyses of the secretory phase, which could improve our understanding of reproductive disorders and inform decisions with regards to any required medical treatments or lack thereof.
Third, chapter 5 describes a comparative approach, which showed that differentially open chromatin regions of bulk ATAC-Seq data can be used as a signature for the recognition of global chromatin states. Moreover, such comparisons can be effective even across species, providing for a valuable method that can be used to extend standard chromatin accessibility analyses. As such, this method could be used in any scenario that aims to compare chromatin states arising from similar treatment conditions across two or more datasets, possibly even for more distant species.
Item Type: | Thesis (PhD) | ||||
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Subjects: | Q Science > QH Natural history > QH426 Genetics | ||||
Library of Congress Subject Headings (LCSH): | Epigenetics, Gene expression -- Research -- Methodology, Genetic transcription -- Research -- Methodology, Computational biology | ||||
Official Date: | March 2020 | ||||
Dates: |
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Institution: | University of Warwick | ||||
Theses Department: | School of Life Sciences | ||||
Thesis Type: | PhD | ||||
Publication Status: | Unpublished | ||||
Supervisor(s)/Advisor: | Ott, Sascha ; Brosens, Jan J. | ||||
Format of File: | |||||
Extent: | xiii, 167 leaves : illustrations, charts | ||||
Language: | eng |
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