Abstract

The management and analysis of the data produced by high-throughput technologies are challenging. This paper discuss multiple hypothesis testing by focusing on developing and applying computationally intensive techniques to achieve the goal of simultaneous tests for each spotID the null hypothesis of no association between the expression levels and the responses or covariates. The software provides features where the user controls the amount of data that can be used for analyzing. The software also produce graph of the output which provide the user with easy viewing of the results.

Library of Congress Subject Headings

Gene expression--Data processing; DNA microarrays; Genomics; Proteomics

Publication Date

11-1-2008

Document Type

Thesis

Department, Program, or Center

Thomas H. Gosnell School of Life Sciences (COS)

Advisor

Skuse, Gary

Comments

Note: imported from RIT’s Digital Media Library running on DSpace to RIT Scholar Works. Physical copy available through RIT's The Wallace Library at: QH450 .K36 2008

Campus

RIT – Main Campus

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