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BIOINFORMATICS
2006

Maximum significance clustering of oligonucleotide microarrays

8 years 10 months ago
Maximum significance clustering of oligonucleotide microarrays
Affymetrix high-density oligonucleotide microarrays measure expression of DNA transcripts using probesets, i.e. multiple probes per transcript. Usually, these multiple measurements are transformed into a single probeset expression level before data analysis proceeds; any information on variability is lost. In this work we demonstrate how individual probe measurements can be used in a statistic for differential expression. Furthermore, we show how this statistic can serve as a clustering criterion. A novel clustering algorithm using this maximum significance criterion is demonstrated to be more efficient with the measured data than competing techniques for dealing with repeated measurements, especially when the sample size is small.
Dick de Ridder, Frank J. T. Staal, Jacques J. M. v
Added 10 Dec 2010
Updated 10 Dec 2010
Type Journal
Year 2006
Where BIOINFORMATICS
Authors Dick de Ridder, Frank J. T. Staal, Jacques J. M. van Dongen, Marcel J. T. Reinders
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