divergences David Penny Phylomania Nov 2013 The mathematicos - PowerPoint PPT Presentation

Loss of information at deeper divergences David Penny Phylomania Nov 2013 The mathematicos caused the problem!!! Now they should solve it! Okay, maybe we could help them, Here are some ideas Need relative – not absolute - information

the comfort zone ML Int ML Rel Ml av ML ML an MP ML ML ep MP MP popn classic phylogeny deep phylogeny

Markov models - Loss of information can we go further back in time?

damned eukaryotes!

Calculated results, Δ ≤ ¼ + ne -qt 0.01 0.005 0.002 0.001 1 0.8 0.6 0.4 0.2 0 1 10 100 1000 10000 -0.2

1. simulation results with covarion model 120% d=0.001 d=0.100 100% d=0.500 percentage of trees correct d=1.000 d=2.000 80% d=5.000 infinite 60% 40% 20% 0% 0.1 1 10

simulation results with standard model 1 number of internal edges correct, out of 6 6 neighbor joining, 9 taxa, 1000 columns, i.i.d. 5 4 3 0.5 2 1 0 0 5 8 13 20 32 50 80 125 200 320 500 790 1250 2000 millions of years (log scale)

1 idea, delete fast sites If there were a mixture of a) faster evolving sites, and b) and we could identify them c) and remove them would that help go further back in time?

deleting faster sites

Ancestral Sequence Reconstruction Giardia animals plants

2, 3, testing Ancestral Sequence Reconstr- uction vaults 3-D info

subgroups X and Y a x a y a b c d e k l m n o subgroup X subgroup Y

4. gene length vs similarity

5, Weighting i j 3 4 5 6 7 8 9 0 1 2 f 1 a . . . . a . . . . . . f 2 . . . . . a . . . . a . upper bound = 17 f 3 . . . . . a . . . . . a f 4 . . . . . a . . . . . . g 1 . a a a a . a a . . . . ? g 2 a a a a a . . a . . a . h 1 . . a a a . . . a a . . 13 h 2 . . a . a . . . a a . . lower bound = 12 h 3 a . . a a . . . a a . . i j i j . . . a Would weighting by incompatibilities a . a a help?

information from sequence order not used Alignment Reordered Alignment original sequence order shuffled/reordered AIIFLNSALGPSPELFPIILATKVL ASAGPSPPATPLLIIIILLFFNEKV AIMFLNSALGPPTELFPVILATKVL ASAGPPTPATPLLIMVILLFFNEKV SIMFLNHTLNPTPELFPIILATETL SHTNPTPPATPLLIMIILLFFNEET TILFLNSSLGLQPEVTPTVLATKTL TSSGLQPPATPLLILTVLVTFNEKT TLLFLNSMLKPPSELFPIILATKTL TSMKPPSPATPLLLLIILLFFNEKT ALLFLNSTLNPPTELFPLILATKTL ASTNPPTPATPLLLLLILLFFNEKT AILFLNSFLNPPKEFFPIILATKIL ASFNPPKPATPLLILIILFFFNEKI c! ways to reorder alignment shuffle by columns & by taxa 6. So, could we use ‘words’ 7. Alphabet of 2, 3, 4, 5, … letters reduction