DNA Phylogeny. Signals and Systems in Biology Kushal EE, IIT Delhi
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1 DNA Phylogeny Signals and Systems in Biology Kushal EE, IIT Delhi
2 Phylogenetics Grouping and Division of organisms Keeps changing with time Splitting, hybridization and termination Cladistics : Methods to determine phylogeny
3 Phylogenetics Grouping and Division of organisms Keeps changing with time Splitting, hybridization and termination Cladistics : Methods to determine phylogeny
4 Phylogenetics Grouping and Division of organisms Keeps changing with time Splitting, hybridization and termination Cladistics : Methods to determine phylogeny
5 Phylogenetics Grouping and Division of organisms Keeps changing with time Splitting, hybridization and termination Cladistics : Methods to determine phylogeny
6 Phylogenetics Grouping and Division of organisms Keeps changing with time Splitting, hybridization and termination Cladistics : Methods to determine phylogeny
7 Tree showing evolutionary relationships between various species Taxa joined if they are believed to have a common ancestor
8 Phylogenetic Tree : Rooted and Unrooted
9 Methods of Phylogenetic Analysis Morphological Analysis Average body size Lengths or sizes of specific physical features Certain kinds of behaviour Comparison of RNA sequences : 18S ribosomal RNA Computational Analysis Compute distance matrix Alignment based and Alignment-Free Methods Generate phylogenetic tree based on this matrix Neighbor joining Fitch-Margoliash method Using independent information Maximum Parsimony
10 Methods of Phylogenetic Analysis Morphological Analysis Average body size Lengths or sizes of specific physical features Certain kinds of behaviour Comparison of RNA sequences : 18S ribosomal RNA Computational Analysis Compute distance matrix Alignment based and Alignment-Free Methods Generate phylogenetic tree based on this matrix Neighbor joining Fitch-Margoliash method Using independent information Maximum Parsimony
11 Methods of Phylogenetic Analysis Morphological Analysis Average body size Lengths or sizes of specific physical features Certain kinds of behaviour Comparison of RNA sequences : 18S ribosomal RNA Computational Analysis Compute distance matrix Alignment based and Alignment-Free Methods Generate phylogenetic tree based on this matrix Neighbor joining Fitch-Margoliash method Using independent information Maximum Parsimony
12 Methods of Phylogenetic Analysis Morphological Analysis Average body size Lengths or sizes of specific physical features Certain kinds of behaviour Comparison of RNA sequences : 18S ribosomal RNA Computational Analysis Compute distance matrix Alignment based and Alignment-Free Methods Generate phylogenetic tree based on this matrix Neighbor joining Fitch-Margoliash method Using independent information Maximum Parsimony
13 Methods of Phylogenetic Analysis Morphological Analysis Average body size Lengths or sizes of specific physical features Certain kinds of behaviour Comparison of RNA sequences : 18S ribosomal RNA Computational Analysis Compute distance matrix Alignment based and Alignment-Free Methods Generate phylogenetic tree based on this matrix Neighbor joining Fitch-Margoliash method Using independent information Maximum Parsimony
14 Methods of Phylogenetic Analysis Morphological Analysis Average body size Lengths or sizes of specific physical features Certain kinds of behaviour Comparison of RNA sequences : 18S ribosomal RNA Computational Analysis Compute distance matrix Alignment based and Alignment-Free Methods Generate phylogenetic tree based on this matrix Neighbor joining Fitch-Margoliash method Using independent information Maximum Parsimony
15 Methods of Phylogenetic Analysis Morphological Analysis Average body size Lengths or sizes of specific physical features Certain kinds of behaviour Comparison of RNA sequences : 18S ribosomal RNA Computational Analysis Compute distance matrix Alignment based and Alignment-Free Methods Generate phylogenetic tree based on this matrix Neighbor joining Fitch-Margoliash method Using independent information Maximum Parsimony
16 Methods of Phylogenetic Analysis Morphological Analysis Average body size Lengths or sizes of specific physical features Certain kinds of behaviour Comparison of RNA sequences : 18S ribosomal RNA Computational Analysis Compute distance matrix Alignment based and Alignment-Free Methods Generate phylogenetic tree based on this matrix Neighbor joining Fitch-Margoliash method Using independent information Maximum Parsimony
17 Methods of Phylogenetic Analysis Morphological Analysis Average body size Lengths or sizes of specific physical features Certain kinds of behaviour Comparison of RNA sequences : 18S ribosomal RNA Computational Analysis Compute distance matrix Alignment based and Alignment-Free Methods Generate phylogenetic tree based on this matrix Neighbor joining Fitch-Margoliash method Using independent information Maximum Parsimony
18 Methods of Phylogenetic Analysis Morphological Analysis Average body size Lengths or sizes of specific physical features Certain kinds of behaviour Comparison of RNA sequences : 18S ribosomal RNA Computational Analysis Compute distance matrix Alignment based and Alignment-Free Methods Generate phylogenetic tree based on this matrix Neighbor joining Fitch-Margoliash method Using independent information Maximum Parsimony
19 Methods of Phylogenetic Analysis Morphological Analysis Average body size Lengths or sizes of specific physical features Certain kinds of behaviour Comparison of RNA sequences : 18S ribosomal RNA Computational Analysis Compute distance matrix Alignment based and Alignment-Free Methods Generate phylogenetic tree based on this matrix Neighbor joining Fitch-Margoliash method Using independent information Maximum Parsimony
20 Methods of Phylogenetic Analysis Morphological Analysis Average body size Lengths or sizes of specific physical features Certain kinds of behaviour Comparison of RNA sequences : 18S ribosomal RNA Computational Analysis Compute distance matrix Alignment based and Alignment-Free Methods Generate phylogenetic tree based on this matrix Neighbor joining Fitch-Margoliash method Using independent information Maximum Parsimony
21 Methods of Phylogenetic Analysis Morphological Analysis Average body size Lengths or sizes of specific physical features Certain kinds of behaviour Comparison of RNA sequences : 18S ribosomal RNA Computational Analysis Compute distance matrix Alignment based and Alignment-Free Methods Generate phylogenetic tree based on this matrix Neighbor joining Fitch-Margoliash method Using independent information Maximum Parsimony
22 Neighbor Joining (NJ)
23 Maximum Parsimony Number of evolutionary events necessary to explain the observed differences Every evolutionary event has an associated cost Locate a tree with the minimum cost Not every event is equally likely NP-hard problem!! Heuristic search methods for the cheapest tree
24 Maximum Parsimony Number of evolutionary events necessary to explain the observed differences Every evolutionary event has an associated cost Locate a tree with the minimum cost Not every event is equally likely NP-hard problem!! Heuristic search methods for the cheapest tree
25 Maximum Parsimony Number of evolutionary events necessary to explain the observed differences Every evolutionary event has an associated cost Locate a tree with the minimum cost Not every event is equally likely NP-hard problem!! Heuristic search methods for the cheapest tree
26 Maximum Parsimony Number of evolutionary events necessary to explain the observed differences Every evolutionary event has an associated cost Locate a tree with the minimum cost Not every event is equally likely NP-hard problem!! Heuristic search methods for the cheapest tree
27 Maximum Parsimony Number of evolutionary events necessary to explain the observed differences Every evolutionary event has an associated cost Locate a tree with the minimum cost Not every event is equally likely NP-hard problem!! Heuristic search methods for the cheapest tree
28 Maximum Parsimony Number of evolutionary events necessary to explain the observed differences Every evolutionary event has an associated cost Locate a tree with the minimum cost Not every event is equally likely NP-hard problem!! Heuristic search methods for the cheapest tree
29 Maximum Parsimony Number of evolutionary events necessary to explain the observed differences Every evolutionary event has an associated cost Locate a tree with the minimum cost Not every event is equally likely NP-hard problem!! Heuristic search methods for the cheapest tree
30 Genetic Distance X,Y : Two populations for which L loci have been sampled X u,y u : Frequency of uth allele at the lth location Nei s method : D a = l u X u Y u ln ( l u X 2 u )( l u Y 2 u ) ( Cavalli-Sforza chord measure : D CH = 2 2 π L l ) X u Y u u
31 Genetic Distance X,Y : Two populations for which L loci have been sampled X u,y u : Frequency of uth allele at the lth location Nei s method : D a = l u X u Y u ln ( l u X 2 u )( l u Y 2 u ) Cavalli-Sforza chord measure : ( D CH = 2 2 π L l ) X u Y u u
32 Genetic Distance X,Y : Two populations for which L loci have been sampled X u,y u : Frequency of uth allele at the lth location Nei s method : D a = l u X u Y u ln ( l u X 2 u )( l u Y 2 u ) ( Cavalli-Sforza chord measure : D CH = 2 2 π L l ) X u Y u u
33 Genetic Distance : Information ( ) K (x) K x y d (x,y) = 1 K (xy) K ( ) : Kolmogorov Complexity d (x,y) satisfies triangle inequality d (x,y) d (y,x) : non-trivial proof M. Li et. al., Bioinformatics 2001
34 Genetic Distance : Information ( ) K (x) K x y d (x,y) = 1 K (xy) K ( ) : Kolmogorov Complexity d (x,y) satisfies triangle inequality d (x,y) d (y,x) : non-trivial proof M. Li et. al., Bioinformatics 2001
35 Genetic Distance : Information ( ) K (x) K x y d (x,y) = 1 K (xy) K ( ) : Kolmogorov Complexity d (x,y) satisfies triangle inequality d (x,y) d (y,x) : non-trivial proof M. Li et. al., Bioinformatics 2001
36 Genetic Distance : Correlation Based I (k) = p (k) p (k) (i,j) (i,j) log 4 p (i)p (j) i,j S S = {A,T,G,C} M. Dehnert et. al., J. Computational Biology 2005
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