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Selecting Restriction Enzymes for Terminal Restriction Fragment Length Polymorphism based on Phylogenetic Distance. Present: Mei, Ko -Jen N18981246 機械博二. Outline. Introduction Algorithm Skeleton Distinct Matrix Establishment for Clusters
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Selecting Restriction Enzymes for Terminal Restriction Fragment Length Polymorphism based on PhylogeneticDistance Present: Mei, Ko-Jen N18981246 機械博二
Outline • Introduction • Algorithm • Skeleton • Distinct Matrix Establishment for Clusters • Distinct Matrix Establishment for Sample Vector of Restriction Enzymes • Match and Weight • Program Application • Discussion • Conclusion
Introduction • What is T-RFLP? • What is phylogenetic distance matrix? • What is restriction enzyme? • What is the concern of selecting restriction enzymes for T-RFLP? • How to solve this problem in the past?
Algorithm -Distinct Matrix Establishment for Sample Vector of Restriction Enzymes (I)
Algorithm -Distinct Matrix Establishment for Sample Vector of Restriction Enzymes (II)
Algorithm- Match and Weight (I) Artificial Weight Natural Weight
Discussion (I) • Find the best mask for a target vector from several candidate vectors • Why natural weight meaningful for identical element? • Difference between classes higher then difference within class • (Cluster, Restriction Enzyme) = (SAME, SAME) does not influence the result significantly • The distinctibility is remained
Discussion (II) • How artificial weight matrix defined? • Distinctibility for species • (Cluster, Restriction Enzyme) = (DIFFERENT, DIFFERENT) • (Cluster, Restriction Enzyme) = (DIFFERENT, SAME) • Distinctibility for clusters • (Cluster, Restriction Enzyme) = (DIFFERENT, DIFFERENT) • Identity within cluster • (Cluster, Restriction Enzyme) = (SAME SAME) • Not so important; weight it! • Since the importance lower than distinctibility, the weight value is usually within 0~1.
Conclusion • Choosing the most identical vector • from a set of sample vectors • to match the given clusters • applied for choosing restriction enzymes • according to the clusters • clusters can be achieved • by User-defined • by phylogenetic distance matrix • weighting can be achieved • according to phylogeneticdistance matrix • according to artificial weight. • The application can provide an easy environment to manipulate clusters and selecting method.