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University of Southern California Dissertations and Theses
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Bayesian analysis of transcriptomic and genomic data
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Bayesian analysis of transcriptomic and genomic data
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Abstract (if available)
Abstract
Bayesian methods offer a way of doing a fully probabilistic analysis for inference problems and for dealing with uncertainty. They offer a number of advantages over more conventional statistical techniques and have become widely used in the fields of genetics, genomics, bioinformatics and computational systems biology, in an effort to make sense of complex noisy data. Here, we describe an application area dealing with modelling spatial patterning in developing Drosophila embryo. In addition, after describing an analysis of association mapping in chickpea hybrids, we provide a perspective on how to integrate quantitative biology and systems biology approaches to increase power in association mapping studies. Finally, I take a digression to describe a study on transposable element expression and chromatin accessibility in human cancer cells.
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Asset Metadata
Creator
Zubair, Asif
(author)
Core Title
Bayesian analysis of transcriptomic and genomic data
School
College of Letters, Arts and Sciences
Degree
Doctor of Philosophy
Degree Program
Computational Biology and Bioinformatics
Publication Date
05/09/2019
Defense Date
03/07/2019
Publisher
University of Southern California
(original),
University of Southern California. Libraries
(digital)
Tag
approximate Bayesian computation,Bayesian model selection,chickpea,Drosophila,gap genes,GWAS,leukaemia,nested association mapping,OAI-PMH Harvest,transposable elements
Format
application/pdf
(imt)
Language
English
Contributor
Electronically uploaded by the author
(provenance)
Advisor
Nuzhdin, Sergey (
committee chair
), Marjoram, Paul (
committee member
), Rosen, Gary (
committee member
)
Creator Email
asif.zubair@gmail.com,asifzuba@usc.edu
Permanent Link (DOI)
https://doi.org/10.25549/usctheses-c89-157543
Unique identifier
UC11662230
Identifier
etd-ZubairAsif-7428.pdf (filename),usctheses-c89-157543 (legacy record id)
Legacy Identifier
etd-ZubairAsif-7428.pdf
Dmrecord
157543
Document Type
Dissertation
Format
application/pdf (imt)
Rights
Zubair, Asif
Type
texts
Source
University of Southern California
(contributing entity),
University of Southern California Dissertations and Theses
(collection)
Access Conditions
The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...
Repository Name
University of Southern California Digital Library
Repository Location
USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA
Tags
approximate Bayesian computation
Bayesian model selection
chickpea
Drosophila
gap genes
GWAS
leukaemia
nested association mapping
transposable elements