Inferring phylogenetic trees

Prof. William Stafford NobleDepartment of Genome Sciences

Department of Computer Science and EngineeringUniversity of Washington

thabangh@gmail.com

One-minute responses• I did not understand anything in the Gibbs sampling and the second method.• The class was quite OK now. Understood most important things.• I understood 50% of the Python part. But I am a bit confused about the goal of the

programs.• Please send us the slides immediately after lecture.

– I put the slides on the website during the Python half of the class. Hit “refresh” on the web browser to see them.

• I didn’t understand clearly converting scores to p-values, more especially putting 1 and 2. Otherwise everything was clear.

• I think we should go a little bit slower.• I didn’t understand the EM and Gibbs.• The concept of EM and Gibbs sampling are really very important. Please go in

depth on them.• Python sessions are still fine as usual.• These algorithms are complex. Could you please explain them with a bit of some

examples?• I didn’t understand the second Python problem.• Emile must not mark our assessment on the programming part.

Revision - Gibbs

Motif occurrences

Randomly select

1. Randomly discard one sequence

2. Build PSSM from remaining sequences• Counts• Add pseudocounts• Normalize

1. Scan discarded sequence with PSSM

2. Choose new occurrence according to resulting probabilities

sequences

Revision - EM

Motif occurrences

Randomly select

1. Counts2. Add pseudocounts3. Normalize4. Divide by background5. Take log2

1. Scan each sequence with PSSM

2. Take top-scoring occurrence

sequences

Phylogenetic inference

RabbitDoveLionDonkey

Outline

• Parsimony• Distance methods

– Computing distances– Finding the tree

• Maximum likelihood

Selecting a method

Chooseset of

relatedsequences

Obtainmultiple

sequencealignment

Is therestrong

sequencesimilarity?

Maximumparsimonymethods

Is there clearlyrecognizable

sequencesimilarity

Maximumlikelihoodmethods

Distancemethods

Maximum parsimony

for each possible treecompute the parsimony score

return the tree with the best score

Enumerating these trees can take a very

long time

Computing this score is straightforward

How many trees?

• With four sequences: 3 unrooted trees

• With five sequences: 15 unrooted trees.• With seven sequences: 954 unrooted trees.

Computing parsimony scoresScer A G A A A A A T A A C T T T C T C A T G

Spar G G A A A A A T A A C T T T C T G A C A

Smik A A A A T A A C T T C T C A A C A A T ASkud A T C T T G A T C C C T T G T G T T G A

Scer = A Smik = A

Spar = G Skud = A

Scer = A Smik = A

Spar = G Skud = A

Score = 1

Scer = A Smik = A

Spar = G Skud = A

Scer = A Spar = G

Smik = A Skud = A

Scer = A Smik = A

Skud = A Spar = G

Score = 1

This site is uninformative, because all the trees have the same score.

Scer = Smik =

Spar = Skud =

Scer = Spar =

Smik = Skud =

Scer = Smik =

Skud = Spar =

Score = ?

Scer = G Smik = A

Spar = G Skud = T

Scer = G Spar = G

Smik = A Skud = T

Scer = G Smik = A

Skud = T Spar = G

Score = 2

Scer = Smik =

Spar = Skud =

Scer = Spar =

Smik = Skud =

Scer = Smik =

Skud = Spar =

Score = ?

Scer = A Smik = T

Spar = A Skud = T

Scer = A Spar = A

Smik = T Skud = T

Scer = A Smik = T

Skud = T Spar = A

Score = 1

Score = 2

This tree is best.

1 2 1 1 1 1 0 1 2 2 0 0 1 2 2 2 3 1 2 1

Scer Smik

Spar Skud

Total = 26

1 2 1 1 2 1 0 1 2 2 0 0 1 2 2 2 3 1 3 1

Scer Spar

Smik Skud

Total = 28

Parsimony software

• In general, the most widely used programs for phylogenetic analysis are– Phylip (Joe Felsenstein)– PAUP (Jim Swofford)– MacClade (David and Wayne Maddison)

• All three do parsimony. Only Phylip is free.

Previous one-minute responses• How many sequences are usually analyzed by

parsimony methods?– Exhaustively, probably tens of sequences. With heuristic

search methods, you can analyze arbitrarily many, but you lose the guarantee that you’re finding the most parsimonious tree.

• What do good parsimony scores look like?– It depends upon how many sequences are involved, and

how divergent they are.• Why doesn’t the parsimony method take into

account transitions versus transversions?– It can; I presented the simplest version.

Jukes-Cantor model• Assume the same

probability of change at all positions and all times.

• dAB is the proportion of changed sites in the alignment.

• KAB is the distance between sequences A and B.

ABAB dK

Problem #1

• Write a program jukes-cantor.py that takes as input a pairwise sequence alignment and prints the Jukes-Cantor distance. Skip sites that contain gaps.

> cat twoseqs.txtACGTACCG> python jukes-cantor.py twoseqs.txt0.823959

ABAB dK

Problem #2• Generalize your previous program to work for a multiple

sequence alignment.> cat threeseqs.txtACGTACTGACGG> python jukes-cantor-matrix.py threeseqs.txt 0.000 0.824 0.304 0.824 0.000 0.304 0.304 0.304 0.000 > jukes-cantor-multiple.py moreseqs.txt 0.000 0.233 0.383 0.233 0.233 0.000 0.824 0.572 0.383 0.824 0.000 0.107 0.233 0.572 0.107 0.000

Inferring phylogenetic trees

Documents

Phylogenetic Trees Lecture 4

Inferring Evolutionary Process from Phylogenetic Tree Shape....

BIS2C. Biodiversity and the Tree of Life. 2014. L4....

Phylogenetic Trees Lecture 1

Inferring Rooted Species Trees

2004 Phylogenetic Trees Made Easy

Building phylogenetic trees

Drawing Phylogenetic Trees*

Terminology of phylogenetic trees Types of phylogenetic...

Automatic and manual sequence alignment Inferring...

Terminology of Phylogenetic Trees

Inferring phylogenetic trees: Distance methods

. Maximum Likelihood (ML) Parameter Estimation with...

Phylogenetic Trees Lecture 2

Inferring Adaptive Landscapes from Phylogenetic Trees: A ...

Bioinformatics Phylogenetic...