DNA Gel Image Analysis using Clustering Techniques and Statistics

A. Bari (Italy), I. Elouafi (Syria), A. Martin (Spain), B. Boulouha, L. Sikaoui (Morocco), J.L. Gonz


DNA gel image analysis, AFLP markers, K-meansclustering, Hierarchical clustering


The DNA electrophoresis gel analysis is used to provide insights into the genetic variation, including phylo geographic pattern. The electrophoresis process allows molecules, such as DNA fragments, to migrate through gel, under the influence of an electric current. DNA electrophoresis gel images generated, with the Amplified Fragment Length Polymorphism (AFLP) technique, are characterized by many bands in a gel and thus require tremendous work by the user to complete their interpretation. AFLP is a polymerase chain reaction (PCR)-based fingerprinting technology where PCR amplifies DNA fragments that are visualized on gels. To reduce the interaction in the detection and interpretation of DNA restriction fragments from gel images an automated procedure was carried out. The procedure is similar to that applied in the fields of pattern recognition and image analysis. First the gel images were pre processed by converting them to vectors and then their features were classified using different clustering techniques in combination with statistics. The clustering is based on the assumptions that electrophoresis gel image consists of layers where each layer is a cluster of pixels or bands of similar intensity values. For validation the experiment was conducted on AFLP gel images of olive (Olea europaea L.) and durum wheat (Triticum turgidum L. var. durum). The results show that this technique detected bands even when the gel image presents lane to lane variations and background effects due to brightness. Further work on the automation process would lead towards objective and rapid assessment of genetic diversity by reducing the user interaction to complete DNA gel image analysis.

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