Date of Award

Spring 2013

Document Type

Thesis

Degree Name

Master of Science in Bioinformatics - (M.S.)

Department

Computer Science

First Advisor

Zhi Wei

Second Advisor

Usman W. Roshan

Third Advisor

Dimitri Theodoratos

Abstract

RNA-sequencing refers to the use of high throughput sequencing technologies that are used to sequence cDNA in order to get the complete information of a sample’s RNA content. The objective of this study is to analyze this data in different aspects and to characterize gene expression. Besides this characterization, the data was also used to investigate the effect of sequencing depth on gene expression measurements.

This research focuses on quantitative measurement of expression levels of genes and their transcripts. In this study, complementary DNA fragments of cultured human melanoma cells are sequenced and a total of 139,501,106 million 200-bp reads from two samples affected with the disease are obtained. The RNA-seq is performed by first mapping the sequence reads to the reference human genome sequence (NCBI 36.1 [hg19] assembly) using Tophat and Bowtie software’s. Then, using Cufflinks software the alignments are assembled into gene transcripts and relative abundances are obtained. Finally, differentially expressed genes are found by comparing the affected samples with a control sample.

The findings are represented in the form of graphs, which best signify the gene expression. This graphical representation of the results will allow the readers to study the expression and structure of genes in human melanoma cells.

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