A wholly defined Agilent microarray spike-in dataset.

Qianqian Zhu, Jeffrey C Miecznikowski, Marc S Halfon
Author Information
  1. Qianqian Zhu: Department of Biochemistry, Department of Biostatistics, State University of New York at Buffalo, Buffalo, NY 14214, USA. qzhu@buffalo.edu

Abstract

MOTIVATION: Spike-in datasets provide a valuable resource for assessing and comparing among competing microarray analysis strategies. Our previous wholly defined spike-in datasets, the Golden and Platinum Spikes, have provided insights for the analysis of Affymetrix GeneChips. However, a similar dataset, in which all cRNA identities and relative levels are known prospectively, has not been available for two-color platforms.
RESULTS: We have generated a wholly defined spike-in dataset for Agilent microarrays consisting of 12 arrays with more than 2000 differentially expressed, and approximately 3600 background, cRNAs. The composition of this 'Ag Spike' dataset is identical to that of our previous Platinum Spike dataset and therefore allows direct cross-platform comparison. We demonstrate here the utility of the Ag Spike dataset for evaluating different analysis methods designed for two-color arrays. Comparison between the Ag Spike and Platinum Spike studies shows high agreement between results obtained using the Affymetrix and Agilent platforms.
AVAILABILITY: The Ag Spike raw data can be accessed at http://www.ccr.buffalo.edu/halfon/spike/index.html and through NCBI's Gene Expression Omnibus (GEO; accession GSE24866).

Associated Data

GEO | GSE24866

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Grants

  1. R03 LM008941/NLM NIH HHS

MeSH Term

Computational Biology
DNA, Complementary
Oligonucleotide Array Sequence Analysis
ROC Curve

Chemicals

DNA, Complementary

Word Cloud

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