Automatic analysis of agarose gel images

Umesh Adiga, P. S. and Bhomra, A. and Turri, M. G. and Nicod, A. and Datta, S. R. and Jeavons, P. and Mott, R. and Flint, J. (2001) Automatic analysis of agarose gel images. Bioinformatics 17(11):pp. 1084-1089.

Abstract

Motivation: Automatic tools to speed up routine biological processes are very much sought after in bio-medical research. Much repetitive work in molecular biology, such as allele calling in genetic analysis, can be made semi-automatic or task specific automatic by using existing techniques from computer science and signal processing. Computerized analysis is reproducible and avoids various forms of human error. Semi-automatic techniques with an interactive check on the results speed up the analysis and reduce the error.Results: We have successfully implemented an image processing software package to automatically analyze agarose gel images of polymorphic DNA markers. We have obtained up to 90% accuracy for the classification of alleles in good quality images and up to 70% accuracy in average quality images. These results are obtained within a few seconds. Even after subsequent interactive checking to increase the accuracy of allele classification to 100%, the overall speed with which the data can be processed is greatly increased, compared to manual allele classification.Availability: The IDL source code of the software is available on request from jonathan.flint@well.ox.ac.uk