• DocumentCode
    821960
  • Title

    Signal Quality Measurements for cDNA Microarray Data

  • Author

    Bergemann, Tracy L. ; Zhao, Lue Ping

  • Author_Institution
    Div. of Biostat., Univ. of Minnesota, Minneapolis, MN, USA
  • Volume
    7
  • Issue
    2
  • fYear
    2010
  • Firstpage
    299
  • Lastpage
    308
  • Abstract
    Concerns about the reliability of expression data from microarrays inspire ongoing research into measurement error in these experiments. Error arises at both the technical level within the laboratory and the experimental level. In this paper, we will focus on estimating the spot-specific error, as there are few currently available models. This paper outlines two different approaches to quantify the reliability of spot-specific intensity estimates. In both cases, the spatial correlation between pixels and its impact on spot quality is accounted for. The first method is a straightforward parametric estimate of within-spot variance that assumes a Gaussian distribution and accounts for spatial correlation via an overdispersion factor. The second method employs a nonparametric quality estimate referred to throughout as the mean square prediction error (MSPE). The MSPE first smoothes a pixel region and then measures the difference between actual pixel values and the smoother. Both methods herein are compared for real and simulated data to assess numerical characteristics and the ability to describe poor spot quality. We conclude that both approaches capture noise in the microarray platform and highlight situations where one method or the other is superior.
  • Keywords
    DNA; biological techniques; data analysis; measurement errors; molecular biophysics; statistical analysis; Gaussian distribution; MSPE; cDNA microarray data; mean square prediction error; measurement error; measurement reliability quantification; microarray expression data reliability; nonparametric quality estimate; pixel spatial correlation; signal quality measurements; spot quality; spot specific error; spot specific intensity estimates; Data mining; Design for experiments; Gaussian distribution; Gold; Image sequence analysis; Laboratories; Measurement errors; Measurement standards; Semiconductor device measurement; Statistics; Image Analysis; Microarray; Prediction Error; Signal Quality; image analysis.; prediction error; signal quality; Analysis of Variance; Computational Biology; Computer Simulation; Databases, Genetic; Humans; Image Processing, Computer-Assisted; Neoplasms; Normal Distribution; Oligonucleotide Array Sequence Analysis; Signal Processing, Computer-Assisted;
  • fLanguage
    English
  • Journal_Title
    Computational Biology and Bioinformatics, IEEE/ACM Transactions on
  • Publisher
    ieee
  • ISSN
    1545-5963
  • Type

    jour

  • DOI
    10.1109/TCBB.2008.72
  • Filename
    4585354