Date of Award

2011

Degree Type

Thesis

Degree Name

Master of Science

Program

Computer Science

Supervisor

Dr. Lucian Ilie

Second Advisor

Dr. Silvana Ilie

Abstract

The advent of next generation sequencing technologies (NGS) generated a revolution in biological research. However, in order to use the data they produce, new computational tools are needed. Due to significantly shorter length of the reads and higher per-base error rate, more complicated approaches are employed and still critical problems, such as genome assembly, are not satisfactorily solved. We therefore focus our attention on improving the quality of the NGS data. More precisely, we address the error correction issue. The current methods for correcting errors are not very accurate. In addition, they do not adapt to the data. We proposed a novel tool, HiTEC, to correct errors in NGS data. HiTEC is based on the suffix array data structure accompanied by a statistical analysis. HiTEC’s accuracy is significantly higher than all previous methods. In addition, it is the only tool with the ability of adjusting to the given data set. In addition, HiTEC is time and space efficient.

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