Automatic analysis of agarose gel images

Motivation: Automatic tools to speed up routine biological processes are ve ry much sought after in bio-medical research. Much repetitive work in molec ular biology, such as allele calling in genetic analysis, can be made semia utomatic or task specific automatic by using existing techniques from compu ter science and signal processing. Computerized analysis is reproducible an d avoids various forms of human error. Semi-automatic techniques with an in teractive check on the results speed up the analysis and reduce the error. Results: We have successfully implemented an image processing software pack age to automatically analyze agarose gel images of polymorphic DNA markers. We have obtained up to 90% accuracy for the classification of alleles in g ood quality images and up to 70% accuracy in average quality images. These results are obtained within a few seconds. Even after subsequent interactiv e checking to increase the accuracy of allele classification to 100%, the o verall speed with which the data can be processed is greatly increased, com pared to manual allele classification.