VisR: An interactive visualization framework for analysis of sequencing data

Resource type
Thesis type
(Thesis) Ph.D.
Date created
Several tools have been developed to enable biologists to perform initial browsing and exploration of sequencing data. However, the computational tool set for further analyses often requires significant computational expertise to use and many of the biologists with the knowledge needed to interpret these data must rely on programming experts. In this thesis, we focus on addressing this limitation through visualization tools for exploratory analysis of sequencing data and contribute the design and development of two novel systems that are flexible enough to allow a high degree of analysis power, while at the same time are easy to use for non-programmers: (1) a general purpose framework that bridges the gap between the biologists and the bioinformaticians through a system of visual analysis modules that can be rapidly developed and connected together, and (2) a first-of-its-kind system that facilitates visual parameter space analysis for a wide variety of computer models. We start by providing a characterization of the data and an abstraction of the domain tasks in the field of epigenetics and present a design study on development and evaluation of ChAsE, an interactive tool to facilitate analysis and visualization of epigenetic datasets. We will then discuss VisR, a general framework for analysis of sequencing datasets that provides both a computationally rich as well as accessible framework for integrative and interactive analyses through modules called R-apps that utilize packages in R and repositories such as Bioconductor. Our framework provides means for interactive exploration of the results or the R-apps, and supports linking apps to create more complex workflows. It also provides an ecosystem to allow extension and sharing of the apps. We finally present ModEx, a general purpose system for exploring parameters of a variety of computer models. We discuss how the system offers key components of visual parameter space analysis frameworks including parameter sampling, deriving output summaries, and an interactive and customizable exploration interface and explain how it can be used for rapid development of custom solutions for different application domains.
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This thesis may be printed or downloaded for non-commercial research and scholarly purposes.
Scholarly level
Supervisor or Senior Supervisor
Thesis advisor: Zhang, Richard
Thesis advisor: Moller, Torsten
Member of collection
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etd20625.pdf 24.83 MB