Abstract
We describe an exploratory, data-oriented approach for identifying candidates for differential gene expression in cDNA microarray experiments in terms of alpha-outliers and outlier regions, using simultaneous tolerance intervals relative to the line of equivalence (Cy5 = Cy3). We demonstrate the improved performance of our approach over existing single-slide methods using public datasets and simulation studies.
Publication types
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Comparative Study
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Research Support, Non-U.S. Gov't
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Research Support, U.S. Gov't, Non-P.H.S.
MeSH terms
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Analysis of Variance
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Computer Simulation
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DNA Replication / genetics
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DNA, Complementary / genetics
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DNA, Fungal / genetics
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Data Interpretation, Statistical
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Gene Expression Profiling / methods*
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Gene Expression Profiling / statistics & numerical data
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Gene Expression Regulation, Fungal / genetics
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Models, Biological
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Nuclear Proteins / deficiency
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Nuclear Proteins / genetics
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Oligonucleotide Array Sequence Analysis / methods*
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Oligonucleotide Array Sequence Analysis / statistics & numerical data
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Saccharomyces cerevisiae / genetics
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Saccharomyces cerevisiae / metabolism
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Saccharomyces cerevisiae Proteins / genetics
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Transcription Factors / deficiency
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Transcription Factors / genetics
Substances
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DNA, Complementary
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DNA, Fungal
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MAC1 protein, S cerevisiae
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Nuclear Proteins
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Saccharomyces cerevisiae Proteins
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Transcription Factors