A probe-treatment-reference (PTR) model for the analysis of oligonucleotide expression microarrays.

BMC Bioinformatics
Huanying GeLei M Li

Abstract

Microarray pre-processing usually consists of normalization and summarization. Normalization aims to remove non-biological variations across different arrays. The normalization algorithms generally require the specification of reference and target arrays. The issue of reference selection has not been fully addressed. Summarization aims to estimate the transcript abundance from normalized intensities. In this paper, we consider normalization and summarization jointly by a new strategy of reference selection. We propose a Probe-Treatment-Reference (PTR) model to streamline normalization and summarization by allowing multiple references. We estimate parameters in the model by the Least Absolute Deviations (LAD) approach and implement the computation by median polishing. We show that the LAD estimator is robust in the sense that it has bounded influence in the three-factor PTR model. This model fitting, implicitly, defines an "optimal reference" for each probe-set. We evaluate the effectiveness of the PTR method by two Affymetrix spike-in data sets. Our method reduces the variations of non-differentially expressed genes and thereby increases the detection power of differentially expressed genes. Our results indicate that the refere...Continue Reading

References

Jan 3, 2001·Proceedings of the National Academy of Sciences of the United States of America·C Li, W H Wong
Feb 13, 2003·Nucleic Acids Research·Rafael A IrizarryTerence P Speed
Feb 13, 2004·Bioinformatics·Laurent GautierRafael A Irizarry
Oct 6, 2004·Genome Biology·Robert C GentlemanJianhua Zhang
Nov 30, 2004·Clinical Biomechanics·Margaret A FinleyMary M Rodgers
Oct 6, 2005·Nucleic Acids Research·Chao Cheng, Lei M Li

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Methods Mentioned

BETA
chips

Software Mentioned

affy package
LOESS
Affymetrix
affy
RMA
MAS
dChip
Bioconductor
R

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