A Model-Based Background Adjustment for Oligonucleotide Expression Arrays

Abstract

High density oligonucleotide expression arrays are widely used in many areas of biomedical research. Affymetrix GeneChip arrays are the most popular. In the Affymetrix system, a fair amount of further pre-processing and data reduction occurs following the image processing * Zhijin Wu is graduate student and Rafael A. Irizarry is Associate Professor of Biostatistics (E-mail: These arrays use short oligonucleotides to probe for genes in an RNA sample. Typically each gene will be represented by 11-20 pairs of oligonucleotide probes. The first component of these pairs is referred to as a perfect match probe and is designed to hybridize only with transcripts from the intended gene (specific hybridization). However, hybridization by other sequences (non-specific hybridization) is unavoidable. Furthermore, hybridization strengths are measured by a scanner that introduces optical noise. Therefore, the observed intensities need to be adjusted to give accurate measurements of specific hybridization. We have found that the default adhoc adjustment, provided as part of the Affymetrix system, can be improved via the use of estimators derived from a statistical model that uses probe sequence information.A final step in pre-processing is to summarize the probe-level data for each gene to define a measure of expression that represents the amount of the corresponding mRNA species. In this paper we illustrate the practical consequences of not adjusting appropriately for the presence of non-specific hybridization and provide a solution based on our background adjustment procedure. Software that computes our adjustment is available as part of the Bioconductor project

Oxidized LDL immune complexes and oxidized LDL differentially affect the expression of genes involved with inflammation and survival in human U937 monocytic cells

“…Hybridization intensity data were normalized using the GCRMA algorithm (20). Identification of differentially expressed genes and hierarchical clustering were performed using dChip software (21).…”

A review of statistical methods for preprocessing oligonucleotide microarrays

“…Affinity values for any probe sequence can then be calculated from the probe sequence and used to predict and adjust for the probe specific background. This background adjustment is used in preprocessing procedure GCRMA and shown to decrease the bias in expression measurements without much increase of variance (19). Physical models that use the stacking energy of DNA/RNA hybridizations have also been used to predict the hybridization stability of specific and nonspecific bindings.…”

“…These are the most informative probes but may be down weighted as outliers. Multiarray analyses, such as RMA (15), GCRMA (19) and model-based expression index (MBEI) (23), identify outliers using information across arrays. For each probe set, consider a linear model (31) on the background adjusted, normalized and log transformed data of probe j on array i :…”

Von-Hippel-Lindau-Gen-Mutationstypen

“…Dieser Prozess wurde am "Broad Institute of MIT and Harvard Medical School" (Cambridge, USA) durchgeführt. Die Affymetrix-Rohdaten wurden mittels GCRMA normalisiert [19]. "Significance Analysis of Microarrays" [18] wurde angewendet, um differenziell regulierte Gene zwischen kNZK und pNZK, bzw.…”