The New Jersey Institute of Technology's
Electronic Theses & Dissertations Project

Title:	Performance comparison of five RNA-seq alignment tools
Author:	Lu, Yuanpeng
View Online:	njit-etd2013-047 (viii, 13 pages ~ 0.3 MB pdf)
Department:	Department of Computer Science
Degree:	Master of Science
Program:	Bioinformatics
Document Type:	Thesis
Advisory Committee:	Wei, Zhi (Committee chair) Roshan, Usman W. (Committee member) Ammicht, Egbert (Committee member)
Date:	2013-05
Keywords:	RNA-seq alignment tools High throughput sequencing
Availability:	Unrestricted
Abstract:	Aligning millions of short reads to a reference genome is a critical task in high throughput sequencing. In recent years, a large number of mapping algorithms have been developed, all of which have in common that they align a vast number of reads to genomic or transcriptomic sequences. RNA-Seq data is discrete in nature, therefore with reasonable gene models and comparative metrics RNA-Seq data can be simulated to sufficient accuracy to enable meaningful benchmarking of alignment algorithms. To provide guidance in the choice of alignment algorithms, five different alignment tools for RNA-Seq data are evaluated. In order to compare the accuracy and sensitivity of the Bowtie, Bowtie2, GMAP, Tophat and GNUMAP tools, their alignment accuracy for approximately 1 million simulated reads of chromosome one was evaluated using these five alignment tools. Bowtie has the highest accuracy, which is 92.42%, while GMAP has the lowest, which is 49.63%. Tophat has the highest sensitivity , which is 71.35% , while GMAP has the lowest, which is 51.69%.