Estimation of expression levels in spotted microarrays with saturated pixels

Chris A Glasbey, Thorsten Forster, Peter Ghazal

Research output: Contribution to journalArticlepeer-review

Abstract

Digital images obtained by the laser scanning of spotted microarrays often include saturated pixel values. These arise when the scan settings are sufficiently high and some pixels exceed the limit L=65535 and are instead set to L. Failure to adjust for this censoring leads to biased estimates of gene expression levels. To impute censored values, we propose a linear model based on the principal components of uncensored spots on the same array. This is computationally fast, flexible to adapt to distinctive spot shapes and profiles on different arrays, and is shown to be more effective than the polynomial-hyperbolic model in correcting for the bias. The application to biological data demonstrates the potential for enhancing the dynamic range of detection. Fortran90 subroutines implementing these methods are available at http://www.bioss.ac.uk/~chris.
Original languageEnglish
Pages (from-to)Article34
JournalStatistical applications in genetics and molecular biology
Volume6
DOIs
Publication statusPublished - 2007

Keywords

  • Animals
  • Gene Expression Profiling
  • Humans
  • Image Processing, Computer-Assisted
  • Mice
  • Models, Theoretical
  • Oligonucleotide Array Sequence Analysis
  • Principal Component Analysis

Fingerprint

Dive into the research topics of 'Estimation of expression levels in spotted microarrays with saturated pixels'. Together they form a unique fingerprint.

Cite this