Summaries of Affymetrix GeneChip probe level data.

High density oligonucleotide array technology is widely used in many areas of biomedical research for quantitative and highly parallel measurements of gene expression. Affymetrix GeneChip arrays are the most popular. In this technology each gene is typically represented by a set of 11-20 pairs of probes. In order to obtain expression measures it is necessary to summarize the probe level data. Using two extensive spike-in studies and a dilution study, we developed a set of tools for assessing the effectiveness of expression measures. We found that the performance of the current version of the default expression measure provided by Affymetrix Microarray Suite can be significantly improved by the use of probe level summaries derived from empirically motivated statistical models. In particular, improvements in the ability to detect differentially expressed genes are demonstrated.

[1]  John W. Tukey,et al.  Exploratory Data Analysis. , 1979 .

[2]  D. Lockhart,et al.  Expression monitoring by hybridization to high-density oligonucleotide arrays , 1996, Nature Biotechnology.

[3]  Ross Ihaka,et al.  Gentleman R: R: A language for data analysis and graphics , 1996 .

[4]  S. P. Fodor,et al.  High density synthetic oligonucleotide arrays , 1999, Nature Genetics.

[5]  E. Brown,et al.  Genomic analysis of gene expression in C. elegans. , 2000, Science.

[6]  E. Chudin,et al.  Assessment of the relationship between signal intensities and transcript concentration for Affymetrix GeneChip® arrays , 2001, Genome Biology.

[7]  Felix Naef,et al.  Empirical characterization of the expression ratio noise structure in high-density oligonucleotide arrays , 2002, Genome Biology.

[8]  E. Brown,et al.  Quantitative analysis of mRNA amplification by in vitro transcription. , 2001, Nucleic acids research.

[9]  C. Li,et al.  Model-based analysis of oligonucleotide arrays: expression index computation and outlier detection. , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[10]  D. Slonim,et al.  Evaluation of normalization procedures for oligonucleotide array data based on spiked cRNA controls , 2001, Genome Biology.

[11]  Fred A. Wright,et al.  Theoretical and experimental comparisons of gene expression indexes for oligonucleotide arrays , 2002, Bioinform..

[12]  S. Dudoit,et al.  Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. , 2002, Nucleic acids research.

[13]  N. Patil,et al.  DNA hybridization to mismatched templates: a chip study. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[14]  Terence P. Speed,et al.  A comparison of normalization methods for high density oligonucleotide array data based on variance and bias , 2003, Bioinform..

[15]  Rafael A Irizarry,et al.  Exploration, normalization, and summaries of high density oligonucleotide array probe level data. , 2003, Biostatistics.

[16]  Rafael A. Irizarry,et al.  An R Package for Analyses of Affymetrix Oligonucleotide Arrays , 2003 .