Unsupervised assessment of microarray data quality using a Gaussian mixture model |
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| Authors: | Brian E Howard Beate Sick Steffen Heber |
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| Affiliation: | (1) Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA;(2) Institute of Data Analysis and Process Design, Zurich University of Applied Science, Winterthur, Switzerland |
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| Abstract: | Background Quality assessment of microarray data is an important and often challenging aspect of gene expression analysis. This task frequently involves the examination of a variety of summary statistics and diagnostic plots. The interpretation of these diagnostics is often subjective, and generally requires careful expert scrutiny. |
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