SlideServe
Menu
Préférences
© SlideServe · v2026

Phylogenetic Trees

oliana avatar
32 diapositives · 505 Views · Aug 22, 2014

This tutorial covers the construction and analysis of phylogenetic trees, focusing on measuring distances among sequences using distance-based algorithms like the Neighbor-Joining. It details methods such as the Jukes-Cantor distance measure, the Euclidean distance for multiple sequence alignments, and the star structure assumption. Step-by-step, it explains the neighbor-joining algorithm, including pairwise distance calculations and node fusion processes. Examples of potential problems in phylogenetic analysis are highlighted, along with references to relevant software tools like PHYLIP and MEGA.

Phylogenetic Trees - slide 1
01 / 32Phylogenetic Trees
1 / 17

Télécharger la présentation

Phylogenetic Trees
Une image / un lien ci-dessous est fourni (tel quel) pour télécharger la présentation

Politique de téléchargement : le contenu du site vous est fourni TEL QUEL pour votre information et votre usage personnel ; il ne peut être vendu, concédé sous licence ni partagé sur d’autres sites sans l’accord de son auteur.Le contenu vous est fourni TEL QUEL, pour votre information et votre usage personnel uniquement. Téléchargez la présentation en cliquant sur ce lien. Lors du téléchargement, si vous ne parvenez pas à télécharger une présentation, l’éditeur a peut-être supprimé le fichier de son serveur.Pendant le téléchargement, si vous ne parvenez pas à obtenir une présentation, le fichier a peut-être été supprimé par l’éditeur.

F I N

Plus de contenu associé

Transcription de la présentation
  1. Tutorial 6 Phylogenetic Trees

  2. Tutorial 6 Phylogenetic Trees • Measuring distance • Bottom-up algorithm (Neighbor Joining) • Distance based algorithm • Assuming star structure • Not assuming star • Relative distance based

  3. Measuring Distance • Problem: unrelated sequences approach a fraction of difference expected by chance  The distance measure converges. • Jukes-Cantor

  4. Measuring Distance (cont) Euclidean Distance: Given a multiple sequence alignment Calculate the square root of the sum of the score at every position (i) between two sequences (a, b) (the score increases proportionally to the extent of dissimilarity between residues)

  5. a b d c Star Structure Assumption: Divergence of sequences is assumed to occur at constant rate  Distance to root equals

  6. a b d c Basic Algorithm Constructs rooted tree. Distance matrix Initial star diagram 6

  7. a b d c Selection step Choose the nodes with the shortest distance and fuse them. 7

  8. a a c c a Dce Daf a,d e e e f f c,b Dce d Dbf Dde Dde b b d Quick review 8

  9. Neighbor Joining’ (Not assuming equal divergence) • Step by step summary: • Calculate all pairwise distances. • Pick two nodes (i and j) for which the distance is minimal. • Define a new node (x) and re-calculate the distances from the free nodes to the new node. • Calculate Dix and Djx - the distance of the chosen nodes I and J to the new node X, as well as the distance from X to all other nodes. • Continue until two nodes remain – connect with edge.

  10. Pick two nodes for which the distance is minimal (i,j)

  11. 5,6 Node 10 is a new node.

  12. Re-calculate the distances from new node I,j : the fused nodes (5,6) X :a new added node (node 10) m :the remaining nodes in the star

  13. Calculate Dix and Djx r: ~average distance to nodes L : number of leaves left in the tree (leaves nodes representing taxa, sequences,etc)

  14. Calculate Dix and Djx ΣD5k ΣD6k r5=ΣD5k/(L-2)= 3.22406/(9-2)=0.46058 r6=ΣD6k/(L-2)= 3.22758/(9-2)=0.461083

  15. Calculate Dix and Djx D10,5=(D5,6+r5-r6)/2=(0.06088+0.46058-0.461083)/2) = 0.0301886 D10,6=D5,6-D10,5=0.06088-0.0301886=0.0306914

  16. 0.0301886 0.0306914

  17. Step 2 0.080375 0.044625

  18. Step 3 0.069258 0.040447

  19. Step 4

  20. Step 5

  21. Step 6

  22. Step 7

  23. Problems 2 1 0.1 0.1 0.1 0.4 0.4 4 3

  24. Neighbor Joining (Not assuming equal divergence) • Step by step summary: • Calculate all pairwise distances. • Pick two nodes (i and j) for which the relative distance is minimal (lowest). • Define a new node (x) and re-calculate the distances from the free nodes to the new node. • Calculate Dix and Djx - the distance of the chosen nodes I and J to the new node X, as well as the distance from X to all other nodes. • Continue until two nodes remain – connect with edge.

  25. Step 2. Pick two nodes (i and j) for which the relative distance is minimal (lowest).

  26. X J I M • Negative values • As the average distance from the common ancestor to the rest of the nodes increases, Mij has a lower value. • Select pair that produce lowest value • Reevaluate M with every iteration

  27. 2 1 0.1 0.1 0.1 0.4 0.4 4 3

  28. 2 1 0.1 0.1 0.1 0.4 0.4 4 3

  29. X J I M Re-calculate the distances from new node

  30. EXAMPLE Original distance Matrix Relative Distance Matrix (Mij) The Mij Table is used only to choose the closest pairs and not for calculating the distances 30

  31. Problems with phylogenetic trees Bacillus Bacillus Burkholderias Aeromonas Aeromonas Pseudomonas Pseudomonas Burkholderias Lechevaliera Lechevaliera E.coli E.coli Salmonella Salmonella Bacillus Pseudomonas Pseudomonas Aeromonas Burkholderias Burkholderias Aeromonas Bacillus Lechevaliera Lechevaliera E.coli E.coli Salmonella Salmonella

  32. Software PHYLIP http://evolution.gs.washington.edu/phylip.html http://paup.csit.fsu.edu/ PAUP http://www.megasoftware.net/ MEGA3 http://evolution.genetics.washington.edu/phylip/software.html More