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Bioinformatics

Bioinformatics. Ayesha M. Khan. Comparison of different tree-construction methods. Case Study I : Phylogenetic Trees. Get a multiple sequence alignment. C1 C2 C3 S1 A A G S2 A A A S3 G G A S4 A G A.

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Bioinformatics

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  1. Bioinformatics Ayesha M. Khan

  2. Comparison of different tree-construction methods Lec-12

  3. Case Study I : Phylogenetic Trees Get a multiple sequence alignment C1 C2 C3 S1 A A G S2 A AA S3 G G A S4 A G A Construct a Tree using any suitable method (Parsimony, ML, etc..) Lec-12

  4. Evaluation • For example, how confident are we that two sequences are in the same clade? • What is the probability distribution of our confidence of the branches ? • Bootstrap can provide a way of determining this (first thought of by Felsenstein, 1985) Lec-12

  5. Bootstrap: basic idea • Originally, from some list of data, one computes an object. • Create an artificial list by randomly drawing elements from that list. • -Some elements will be picked more than once. • Compute a new object. • Repeat 100-1000 times and look at the distribution of these objects. Lec-12

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  7. Original object O (a tree) is computed from a “list of data” (numbers, sequences, microarray data,….). • Construct a new list, with the same number of elements, from the original list by randomly picking elements from the list. Any one element from the list can be picked any number of times. • Compute new object, call it O1 • Repeat the process many times (typically 100-1000). • The elements {O1 ,O2 , ……} are assumed to be taken from a statistical distribution, so one can compute averages, variances, etc. Lec-12

  8. A model for the bootstrap • Basically, we are calculating the proportion of bootstrap trees agreeing with the original tree. • ‘Agreeing’ refers to the topology of the trees The numbers at the branches are confidence values based on Felsenstein’s bootstrap method. B=200 bootstrap replications Lec-12

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