Date of Award

5-8-2020

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Computer Science

First Advisor

Dr. Alexander Zelikovsky

Second Advisor

Sergey Knyazev

Abstract

For viral outbreaks like the recent COVID-19 outbreak, medical professionals in many areas require to know who infected whom, which variants are drug resistant and what therapy should be selected. To answer these questions, it is necessary to identify viral variants (haplotypes and SNP’s) in patients. A haplotype refers to a combination of alleles or a set of single nucleotide polymorphisms (SNPs) found on the same chromosome. This thesis describes the development and assessment of several pipelines and tools for viral NGS and read data analysis and the effect on the accuracy of the haplotype identification.

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