Abstract
Advances in next generation sequencing (NGS) technologies, in the past half decade, have enabled many novel genomic applications and have generated unprecedented amounts of new knowledge that is quickly changing how biomedical research is being conducted, as well as, how we view human diseases and diversity. As the methods, algorithms and software used to process NGS data are constantly being developed and improved, performing analysis and determining the validity of the results become complex. Moreover, as sequencing moves from being a research tool into a clinical diagnostic tool understanding the performance and limitations of bioinformatics pipelines and the results they produce becomes imperative. This thesis aims to assess the performance of nine bioinformatics pipelines for sequence read alignment, variant calling and genotyping in a Mendelian inherited disease, parent-trio exome sequencing design. A well-characterized reference variant call set from the National Institute of Standards and Technology and the Genome in a Bottle Consortium is be used for producing and comparing the analytical performance of each pipeline on the GRCh37 and GRCh38 human references.
Library of Congress Subject Headings
Exomes; Genomics; Algorithms--Evaluation
Publication Date
9-24-2015
Document Type
Thesis
Student Type
Graduate
Degree Name
Bioinformatics (MS)
Department, Program, or Center
Thomas H. Gosnell School of Life Sciences (COS)
Advisor
Michael V. Osier
Advisor/Committee Member
John M. Ashton
Advisor/Committee Member
Steven R. Gill
Recommended Citation
Corbett, Anthony, "Assessment of Alignment Algorithms, Variant Discovery and Genotype Calling Strategies in Exome Sequencing Data" (2015). Thesis. Rochester Institute of Technology. Accessed from
https://repository.rit.edu/theses/8892
Campus
RIT – Main Campus
Plan Codes
BIOINFO-MS
Comments
Physical copy available from RIT's Wallace Library at QH447 .C67 2015