Dissertation/Thesis Abstract

Efficient identification of disease causative mutations with next generation sequencing technologies
by Maranhao, Bruno, Ph.D., University of California, San Diego, 2015, 836; 3718508
Abstract (Summary)

This thesis presents a multi-faceted approach to analyzing large datasets produced by next generation sequencing techniques for the purpose of identifying the genetic causes of disease phenotypes. The focus of the thesis is recessively inherited retinal degeneration disease phenotypes caused by homozygous mutations, although we also demonstrate the identification of the genetic causes of disease in other inheritance patterns. Additionally, we develop a novel custom capture kit that increases analysis throughput and the judicious use of resources. Software to perform each of the analysis techniques, curate a database of findings, as well as to design novel custom capture kits was designed and packaged as a single application with a graphical user interface available across multiple operating system platforms.

Indexing (document details)
Advisor: Silva, Gabriel
Commitee: Ayyagari, Radha, LaSpada, Albert, Sejnowski, Terrance, Zhang, Kun
School: University of California, San Diego
Department: Bioengineering
School Location: United States -- California
Source: DAI-B 76/12(E), Dissertation Abstracts International
Subjects: Genetics, Bioinformatics
Keywords: Disease causative mutations, Exome, Next generation sequencing, Software
Publication Number: 3718508
ISBN: 978-1-321-98360-9
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