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

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

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?

Comparing Spot and ImaGene Cy5 Intensities

Foreground

Background

Pairwise Comparisons of Cy5 Intensities

Comparing Spot and ImaGene Log Ratios

G

RM 2log

2

loglog 22 GRA

R – background corrected Cy5 signal

G – background corrected Cy3 signal

Pairwise Comparisons of Log Ratios

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

Example 2: Inferences of Data Quality

Concluding Remarks

• Different software programs can produce different outputs.

Different biological inferences?

• Selection of statistically reliable software for image analysis is important.

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