Research Article
New Statistics for Testing Differential Expression of Pathways from Microarray Data
396 downloads
@INPROCEEDINGS{10.1007/978-3-642-02466-5_26, author={Hoicheong Siu and Hua Dong and Li Jin and Momiao Xiong}, title={New Statistics for Testing Differential Expression of Pathways from Microarray Data}, proceedings={Complex Sciences. First International Conference, Complex 2009, Shanghai, China, February 23-25, 2009. Revised Papers, Part 1}, proceedings_a={COMPLEX PART 1}, year={2012}, month={5}, keywords={microarray pathway linear combination test quadratic test de-correlation test rheumatoid arthritis}, doi={10.1007/978-3-642-02466-5_26} }- Hoicheong Siu
Hua Dong
Li Jin
Momiao Xiong
Year: 2012
New Statistics for Testing Differential Expression of Pathways from Microarray Data
COMPLEX PART 1
Springer
DOI: 10.1007/978-3-642-02466-5_26
Abstract
Exploring biological meaning from microarray data is very important but remains a great challenge. Here, we developed three new statistics: linear combination test, quadratic test and de-correlation test to identify differentially expressed pathways from gene expression profile. We apply our statistics to two rheumatoid arthritis datasets. Notably, our results reveal three significant pathways and 275 genes in common in two datasets. The pathways we found are meaningful to uncover the disease mechanisms of rheumatoid arthritis, which implies that our statistics are a powerful tool in functional analysis of gene expression data.
Copyright © 2009–2024 ICST