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Impact of Experimental Noise and Annotation Imprecision on Data Quality in Microarray Experiments

  • Andreas SchererEmail author
  • Manhong Dai
  • Fan Meng
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 972)

Abstract

Data quality is intrinsically influenced by design, technical, and analytical parameters. Quality parameters have not yet been well defined for gene expression analysis by microarrays, though ad interim, following recommended good experimental practice guidelines should ensure generation of reliable and reproducible data. Here we summarize essential practical recommendations for experimental design, technical considerations, feature annotation issues, and standardization efforts.

Key words

Data quality Experimental design Quality parameters Annotation Standardization 

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Genomics, Biomarker Development, Spheromics, KontiolahtiJoensuuFinland
  2. 2.Psychiatry Department and Molecular and Behavioral Neuroscience InstituteUniversity of Michigan, University of MichiganAnn ArborUSA
  3. 3.Psychiatry Department and Molecular and Behavioral Neuroscience InstituteUniversity of Michigan, University of MichiganAnn ArbourUSA

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