Pixel-level signal modelling with spatial correlation for two-colour microarrays

Research output: Contribution to journalJournal articleResearchpeer-review

Statistical models for spot shapes and signal intensities are used in image analysis of laser scans of microarrays. Most models have essentially been based on the assumption of independent pixel intensity values, but models that allow for spatial correlation among neighbouring pixels can accommodate errors in the microarray slide and should improve the model fit. Five spatial correlation structures, exponential, Gaussian, linear, rational quadratic and spherical, are compared for a dataset with 50-mer two-colour oligonucleotide microarrays and 452 probes for selected Arabidopsis genes. Substantial improvement in model fit is obtained for all five correlation structures compared to the model with independent pixel values, and the Gaussian and the spherical models seem to be slightly better than the other three models. We also conclude that for the data set analysed the correlation seems negligible for non-neighbouring pixels.

Original languageEnglish
Article number6
JournalStatistical Applications in Genetics and Molecular Biology
Issue number1
Publication statusPublished - 6 Apr 2005

    Research areas

  • Censored data, Polynomial-hyperbolic model, Spatial correlation, Spotted array

ID: 203909627