1. A Review of Image Analysis Software for Spotted Microarrays Jess Mar Department of Mathematics University of Queensland jcm@maths.uq.edu.au CBiS Microarray/Chip Workshop, Canberra

2. The Image Analysis Process 1. ADDRESSING: identify spot coordinates on the microarray image 2. SEGMENTATION: classification of foreground and background pixels 3. INFORMATION EXTRACTION: foreground & local background estimation of cy3 & cy5 channels, quality control measurements

3.  CSIRO Spot  Affymetrix Jaguar  BioDiscovery ImaGene  DigitalGENOME MolecularWare 1 cDNA slide AF6 Human Melanoma Source: Dr Sean Grimmond, IMB Do These Software Packages Produce the Same Outputs?

4. Comparing Spot and ImaGene Cy5 Intensities Foreground Background

5. Pairwise Comparisons of Cy5 Intensities

6. Comparing Spot and ImaGene Log Ratios R – background corrected Cy5 signal G – background corrected Cy3 signal

7. Pairwise Comparisons of Log Ratios

8. Do These Differences Lead to Consistent Inferences? M versus A plots are useful for highlighting artifacts in the data. saturated spot Example 1: Detecting Spot Saturation

9. Example 2: Inferences of Data Quality

10. Concluding Remarks Different software programs can produce different outputs.  Different biological inferences? Selection of statistically reliable software for image analysis is important.

11. Acknowledgements Institute for Molecular Bioscience Sean Grimmond & SRC Microarray Facility Research School of Biological Sciences Julie Christie Statistical Society of Australia, Inc (Queensland Branch) Centre for Bioinformation Science John Maindonald Sue Wilson Cooperative Research Centre for the Discovery of Genes for Common Human Diseases