Phylogeny

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  • @rdmpage Here's a prototype that pre-processes search queries, to make the interface simpler: http://dl.dropbox.com/u/4180059/treebase/query.html
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  • I've just finished an exercise where the goal was to find phylogenies in TreeBASE and people were totally flummoxed by interface. It's juts not designed for people to actually use.

    Why force the user to tell a computer what something is, get the computer to figure it out? Computers are good at that sort of thing. Just let people type stuff in and figure it out. And no one is going to put in 'dc:identifier=Tx1234', ever. If they put in Tx1234, or a DOI, or whatever, the computer is smart enough to figure that out. If it's a bare number, show the various possible interpretations. At no point should a user have to think.
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  • Slide 50 is my favourite! Do you know the amount of time I spent to make it so that the buttons within the boxes only become active when you check other 'Identifiers' or 'Text search'?

    In an ideal world, this would be a single text box and power users would be able to put 'dc:identifier=Tx1234' in there in the same way that you can put 'filetype:pdf' in a google search.
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  • Parsimony and likelihood pick “best” tree
  • Parsimony and likelihood pick “best” tree
  • Instead of a single best tree we have a probability distribution. Don’t pick the single best tree.
  • http://loco.biosci.arizona.edu/paloverde/paloverde.html
  • http://www.wellcometreeoflife.org/
  • Petra Isenberg, see “Interactive tree comparison for co-located collaborative information visualization” http://www.ncbi.nlm.nih.gov/pubmed/17968069 and http://innovis.cpsc.ucalgary.ca/Research/CollaborativeTreeComparison
  • Image from Mike Sanderson’s Lab (http://loco.biosci.arizona.edu/)
  • http://msdn.microsoft.com/en-us/library/cc645050(v=vs.95).aspx
  • http://iphylo.blogspot.com/2007/08/visualising-very-big-trees-part-iv.html
  • Phylogeny

    1. 1. Phylogeny
    2. 2. 2 Trees and their terms
    3. 3. 3
    4. 4. 4 Tree terminology edge (branch) leaf (terminal node) internal node (hypothetical ancestor) root
    5. 5. 5
    6. 6. 6 Rooting a tree
    7. 7. 7 Order doesn’t matter (trees are like mobiles) A B C D ABCD = AB C D =
    8. 8. 8 Tree description , )( , )( ( A( ,B )), C A CB
    9. 9. Building trees • Maximum parsimony (which tree can explain data with least amount of evolutionary change) • Maximum likelihood (which tree has highest probability of generating observed data) • Bayesian analysis (probability distribution of trees based on prior knowledge and current data)
    10. 10. 11 Types of substitution A G C T transitions transitions transversions
    11. 11. Likelihood 12 A C G T A C G T Observed A C G T A C G T Jukes-Cantor human chimp Predicted by models Kimura 2 parameter A C G T A C G T Hasegawa et al. A C G T A C G T •More parameters = better fit •but, don’t want too many parameters
    12. 12. Probability is different from likelihood
    13. 13. You hear a noise in the ceiling…
    14. 14. Could be elves bowling in the attic
    15. 15. The probability that you have bowling elves is very low…
    16. 16. …but if you did have them, the probability that you would hear them is very high (=likelihood)
    17. 17. Bayesian methods
    18. 18. • Probability of having bowling elves is low (prior probability) • If you have bowling elves, probability that they would make a noise is high (likelihood) • Bayesian methods combine prior probability with likelihood to get posterior probability
    19. 19. Bayesian posterior probabilities 1.0 0.8 0.5 A E B C D
    20. 20. Open problems
    21. 21. Visualisation
    22. 22. There are few constraints on how we can draw trees
    23. 23. X A B C D Y
    24. 24. X B A D C Y We can reorder Y
    25. 25. @broadinstitute
    26. 26. X B A D C Y X is a partial order
    27. 27. X B A D C Y X is a partial order
    28. 28. X: evolutionary distance B A D C Y
    29. 29. X: time B A D C Y
    30. 30. Y X Z? What would third dimension represent?
    31. 31. Paloverde
    32. 32. @wellcometrust
    33. 33. Touching the tree
    34. 34. @dr_pi
    35. 35. Big trees
    36. 36. add
    37. 37. @rdmpage
    38. 38. @rdmpage
    39. 39. Where are the trees?
    40. 40. http://www.treebase.org/
    41. 41. 47 0 1000 2000 3000 4000 5000 6000 7000 1975 1980 1985 1990 1995 2000 2005 Year Cumulative number Rate of growth of phylogenetic knowledge Number of papers with “molecular” and “phylogeny” in Web of Science Number of studies in TreeBASE
    42. 42. Why aren’t we archiving these trees?
    43. 43. How can we find the trees that we have?
    44. 44. TreeBASE interface
    45. 45. TreeBASE interface
    46. 46. Browser
    47. 47. The End

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