Bioinformatics Advance Access originally published online on December 5, 2006
Bioinformatics 2007 23(3):321-327; doi:10.1093/bioinformatics/btl609
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
A distribution free summarization method for Affymetrix GeneChip® arrays
1 Department of Statistical Science, Southern Methodist University Dallas, TX 75275, USA
2 Department of Pathology, University of Texas Southwestern Medical Center Dallas, TX 75390, USA
3 Department of Computer Science, New Mexico Institute of Mining and Technology Socorro NM 87801, USA
*To whom correspondence should be addressed.
| Abstract |
|---|
Motivation: Affymetrix GeneChip arrays require summarization in order to combine the probe-level intensities into one value representing the expression level of a gene. However, probe intensity measurements are expected to be affected by different levels of non-specific- and cross-hybridization to non-specific transcripts. Here, we present a new summarization technique, the Distribution Free Weighted method (DFW), which uses information about the variability in probe behavior to estimate the extent of non-specific and cross-hybridization for each probe. The contribution of the probe is weighted accordingly during summarization, without making any distributional assumptions for the probe-level data.
Results: We compare DFW with several popular summarization methods on spike-in datasets, via both our own calculations and the Affycomp II competition. The results show that DFW outperforms other methods when sensitivity and specificity are considered simultaneously. With the Affycomp spike-in datasets, the area under the receiver operating characteristic curve for DFW is nearly 1.0 (a perfect value), indicating that DFW can identify all differentially expressed genes with a few false positives. The approach used is also computationally faster than most other methods in current use.
Availability: The R code for DFW is available upon request.
Contact: mmcgee{at}smu.edu
Supplementary information: Supplementary data are available at Bioinformatics online.
Associate Editor: Martin Bishop
Received on July 18, 2006; revised on November 6, 2006; accepted on November 24, 2006
This article has been cited by other articles:
![]() |
K. Mashiguchi, E. Urakami, M. Hasegawa, K. Sanmiya, I. Matsumoto, I. Yamaguchi, T. Asami, and Y. Suzuki Defense-Related Signaling by Interaction of Arabinogalactan Proteins and {beta}-Glucosyl Yariv Reagent Inhibits Gibberellin Signaling in Barley Aleurone Cells Plant Cell Physiol., February 1, 2008; 49(2): 178 - 190. [Abstract] [Full Text] [PDF] |
||||
![]() |
K. E. Bjork and K. Kafadar Systematic order-dependent effect in expression values, variance, detection calls and differential expression in Affymetrix GeneChips(R) Bioinformatics, November 1, 2007; 23(21): 2873 - 2880. [Abstract] [Full Text] [PDF] |
||||

