Application of Stellar Photometry To The Analysis of Microarray Images
Mahyar Sabripour1, Christopher I. Amos2, Kevin Coombes
1msabripo@mdanderson.org, Department of Epidemiology, The University of Texas M. D. Anderson Cancer Center; 2camos@request.mdacc.tmc.edu, Department of Epidemiology, The University of Texas M. D. Anderson Cancer Center
The
development of DNA microarray technology gives researchers unique opportunities
to identify genetic factors that may be critical for the prevention and
treatment of cancer. A critical step in the analysis of microarray data is the
quantification of spots on the array platform. Insufficient attention has been
given to the precision and accuracy of spot intensities. The spot intensities
directly influence the results and interpretation of statistical analyses.
Improvements in quantifying spots can directly impact the identification of
genes critical to the development and progression of cancer. This is especially
true with the quantification of faint signals with respect to background noise.
We utilize a stellar photometric model, the Moffat function, to analyze cDNA
membrane microarray images. The Moffat function, a point spread function (PSF),
has traditionally been used in the astronomical community for describing the
intensity distribution of stars. In the current setting, we fit the Moffat
function to cDNA spots on the array and obtain intensity values. The
flexibility of the Moffat function allows the variability seen in cDNA spot
size and shape to be taken into account when quantifying spots. We present
results showing the effectiveness of the Moffat function in quantifying spots
and compare these results with other standard image processing techniques.