UNDERSTANDING BIAS IN NEXT-GENERATION SEQUENCING TECHNOLOGIES AND ANALYSES

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Price, A. (2017). UNDERSTANDING BIAS IN NEXT-GENERATION SEQUENCING TECHNOLOGIES AND ANALYSES. Unc Charlotte Electronic Theses And Dissertations.
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Abstract

The problem of bias resulting from biological and technological sources is one that must be consistently reexamined alongside the development of new technologies and methods of analysis. This dissertation addresses the complexities of bias identification, quantification, and correction in RNA-Seq studies that rely on next generation sequencing technologies and associated analysis methodologies. We identify the cause of GC bias resulting from mRNA secondary structure, examine the problem of non-native reference genome usage when comparing closely related bacterial strains, and provide simulation software that makes it possible to separate the sources of bias and to control for specific factors.

Details
Author

Price, Adam

Title

UNDERSTANDING BIAS IN NEXT-GENERATION SEQUENCING TECHNOLOGIES AND ANALYSES

Physical Description

1 online resource (100 pages) : PDF

Date

2017

Degree Granting Institution

University of North Carolina at Charlotte

Abstract

The problem of bias resulting from biological and technological sources is one that must be consistently reexamined alongside the development of new technologies and methods of analysis. This dissertation addresses the complexities of bias identification, quantification, and correction in RNA-Seq studies that rely on next generation sequencing technologies and associated analysis methodologies. We identify the cause of GC bias resulting from mRNA secondary structure, examine the problem of non-native reference genome usage when comparing closely related bacterial strains, and provide simulation software that makes it possible to separate the sources of bias and to control for specific factors.

Genre

doctoral dissertations

Subjects--Topics

Biology
Bioinformatics
Biophysics

Degree

Ph.D.

Keywords

Bias
Read Alignment
Reference Genome
RNA-SEQ
Secondary Structure
Simulation

Subject Area

Bioinformatics

Advisor(s)

Gibas, Cynthia

Committee Members

Fodor, Anthony
Weller, Jennifer
Shi, Xinghua
Marriot, Ian

Degree Note

Thesis (Ph.D.)--University of North Carolina at Charlotte, 2017.

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Rights Holder Information

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Identifier

Price_uncc_0694D_11320

Permalink

http://hdl.handle.net/20.500.13093/etd:383