Image analysis for cDNA microarrays.
OBJECTIVE
We characterize typical problems encountered in microarray image analysis and present algorithmic approaches dealing with background estimation, spot identification and intensity extraction. Validation of the quality of resulting measurements is discussed.


METHODS
We describe sources for errors in microarray images and present algorithms that have been specifically developed to deal with such experimental imperfections.


RESULTS
For the image analysis of hybridization experiments, discriminating spot regions from a background is the most critical step. Spot shape detection algorithms, intensity histogram methods and hybrid approaches have been proposed. The correctness of final intensity estimates is difficult to verify. Nevertheless, the application of sophisticated algorithms provides a significant reduction of the possible information loss.


CONCLUSIONS
The initial analysis step for array hybridization experiments is the estimation of expression intensities. The quality of this process is crucial for the validity of interpretations from subsequent analysis steps.
Rahnenführer
J
J
Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. rahnenfj@mpi-sb.mpg.de
D000465:Algorithms; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D020869:Gene Expression Profiling / Q000379:methods*; D036281:Genetic Research; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results; D017422:Sequence Analysis, DNA / Q000379:methods*; D013050:Spectrometry, Fluorescence; D013269:Stochastic Processes