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

Title:	Bioinformatics framework for genotyping microarray data analysis
Author:	Zhang, Kai
View Online:	njit-etd2006-046 (xiv, 94 pages ~ 9.0 MB pdf)
Department:	Department of Computer Science
Degree:	Doctor of Philosophy
Program:	Computer Science
Document Type:	Dissertation
Advisory Committee:	Shih, Frank Y. (Committee co-chair) Ma, Qun (Committee co-chair) Cohen, Barry (Committee member) Roshan, Usman W. (Committee member) Wang, Hui-Yun (Committee member)
Date:	2006-01
Keywords:	Bioinformatics Microarray Computer sciences Genotype
Availability:	Unrestricted
Abstract:	Functional genomics is a flourishing science enabled by recent technological breakthroughs in high-throughput instrumentation and microarray data analysis. Genotyping microarrays establish the genotypes of DNA sequences containing single nucleotide polymorphisms (SNPs), and can help biologists probe the functions of different genes and/or construct complex gene interaction networks. The enormous amount of data from these experiments makes it infeasible to perform manual processing to obtain accurate and reliable results in daily routines. Advanced algorithms as well as an integrated software toolkit are needed to help perform reliable and fast data analysis. The author developed a MatlabTM based software package, called TIMDA (a Toolkit for Integrated Genotyping Microarray Data Analysis), for fully automatic, accurate and reliable genotyping microarray data analysis. The author also developed new algorithms for image processing and genotype-calling. The modular design of TIMDA allows satisfactory extensibility and maintainability. TIMDA is open source (URL: http://timda.SF.net and can be easily customized by users to meet their particular needs. The quality and reproducibility of results in image processing and genotype-calling and the ease of customization indicate that TIMDA is a useful package for genomics research.