We have developed methods and identified problems associated with the analysis of data generated by high-density, oligonuceotide gene expression arrays. Our methods are aimed at accounting for many of the sources of variation that make it difficult, at times, to realize consistent results. We present here descriptions of some of these methods and how they impact the analysis of oligonucleotide gene expression array data. We will discuss the process of recognizing the "spots" (or features) on the Affymetrix GeneChip(R) probe arrays, correcting for background and intensity gradients in the resulting images, scaling/normalizing an array to allow array-to-array comparisons, monitoring probe performance with respect to hybridization efficiency, and assessing whether a gene is present or differentially expressed. Examples from the analyses of gene expression validation data are presented to contrast the different methods applied to these types of data.
Ultra-high-throughput sequencing is emerging as an attractive alternative to microarrays for genotyping, analysis of methylation patterns, and identification of transcription fa...
Oligonucleotide arrays can provide a broad picture of the state of the cell, by monitoring the expression level of thousands of genes at the same time. It is of interest to deve...
NetAffx (http://www.affymetrix.com) details and annotates probesets on Affymetrix GeneChip microarrays. These annotations include (i) static information specific to the probeset...
A high-capacity system was developed to monitor the expression of many genes in parallel. Microarrays prepared by high-speed robotic printing of complementary DNAs on glass were...
Epithelial ovarian cancer is the leading cause of death from gynecologic cancer, in part because of the lack of effective early detection methods. Although alterations of severa...
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