where to get help read the manuals and help filescheck out the discussion boards at http://www.rannala.org/phpBB2/

else there is a new program on the block called hy-phy (=hypothesis testing using phylogenetics).

The easiest is probably to run the analyses on the authors datamonkey.

hy-phyResults of an anaylsis using the SLAC approach

more output might still be here

Hy-Phy -Hypothesis Testing using Phylogenies. Using Batchfiles or GUI

Information at http://www.hyphy.org/

Selected analyses also can be performed online at http://www.datamonkey.org/

Example testing for dN/dS in two partitions of the data --John’s dataset

Set up two partitions, define model for each, optimize likelihood

Example testing for dN/dS in two partitions of the data --John’s dataset

The dN/dS ratios for the two partitions are different.

Save Likelihood Functionthenselect as alternative

Example testing for dN/dS in two partitions of the data --John’s dataset

Set up null hypothesis, i.e.:

The two dN/dS are equal

(to do, select both rows and then click the define as equal button on top)

Example testing for dN/dS in two partitions of the data --John’s dataset

Example testing for dN/dS in two partitions of the data --John’s dataset Nam

e and save asNull-hyp.

Example testing for dN/dS in two partitions of the data --John’s dataset

After selecting LRT (= Likelihood Ratio test), the console displays the result, i.e., the beginning and end of the sequence alignment have significantly different dN/dS ratios.

Example testing for dN/dS in two partitions of the data –John’s dataset

Alternatively, especially if the the two models are not nested, one can set up two different windows with the same dataset:

Model 1

Model 2

Example testing for dN/dS in two partitions of the data --John’s dataset

Simulation under model 2, evalutation under model 1, calculate LRCompare real LR to distribution from simulated LR values. The result might look something like this or this

Green - Type A tyrRSRed - Type B tyrRSBlue - Both types of tyrRS

16S rRNA phylogeny colored 16S rRNA phylogeny colored according to tyrRS type according to tyrRS type

Under the assumption that both types were present in the bacterial ancestor and explaining the observed distribution only through gene loss:

133 taxa and 58 gene loss events, 34 losses of type A, 23 of type B

Andam, Williams, Gogarten 2010 PNAS

LGT3State Method

• Generated 1000 bootstrap trees under loss-only model

Real data under HGT model

Simulated under "loss-only" model; likelihood under HGT model

Niket Shah

Important characteristicHundreds of nodeRobust against accidental failuresCoordinated attacks

Networks are everywhereBrain and nerve cellsTiny CellsFood webs and eco-systems

Birth of Scale Free Network

Selection of new nodeWinner takes all

Random versus scale free networks Randomly placed connectionsBell shaped curveSame number of linksHubs (red) Power lawless connection but more links

Growth and preferential attachmentAndreas Wagner of University of New MexicoDavid Fell of Oxford Brookes University of

EnglandEscherichia coli experimentMost connected molecules have early

evolutionary history

Potential implications in MedicineVaccination campaigns against serious

virusesMapping of human cellPrediction of virus or disease if they are

dangerous

Threshold zeroSpreading virusExample of Measles90% of total population

EVERYTHING CAN BE TURNED INTP A HAIRBALL!

The hairball is the icon of systems biology (as the DNA double helix was the icon for molecular biology)

Human proteome, and its binding interactions. Depiction of the data as a hairball, an increasingly familiar image in the biology literature.

Usually "Scale free" only within limits

Comparison between the degree distribution of scale-free networks (O) and random graphs (☐) having the same number of nodes and edges.

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