a web interface to analyse som of bipartitions of gene phylogenies - a walk through

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A Web Interface to analyse SOM of Bipartitions of Gene Phylogenies - A Walk Through J. Peter Gogarten, Maria Poptsova Dept. of Molecular and Cell Biology University of Connecticut Neha Nahar, Lutz Hamel Department of Computer Science and Statistics University of Rhode Island

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A Web Interface to analyse SOM of Bipartitions of Gene Phylogenies - A Walk Through. J. Peter Gogarten, Maria Poptsova Dept. of Molecular and Cell Biology University of Connecticut Neha Nahar, Lutz Hamel Department of Computer Science and Statistics University of Rhode Island. BranchClust. - PowerPoint PPT Presentation

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Page 1: A Web Interface to analyse SOM of   Bipartitions of Gene Phylogenies - A Walk Through

A Web Interface to analyse SOM of

Bipartitions of Gene Phylogenies - A Walk Through

J. Peter Gogarten, Maria Poptsova Dept. of Molecular and Cell Biology

University of Connecticut

Neha Nahar, Lutz Hamel Department of Computer Science and Statistics

University of Rhode Island

Page 2: A Web Interface to analyse SOM of   Bipartitions of Gene Phylogenies - A Walk Through

BranchClust

n Genomes

Super Families

Gene Families

Reconstruct Phylogenetic History for Each Family

Page 3: A Web Interface to analyse SOM of   Bipartitions of Gene Phylogenies - A Walk Through

Data Matrix

Biapartiton #1 (**….….)

… Biapartiton #k(*******..)

Support value vector for a set #1 of orthologous genes P11 … P1k

Support value vector for a set #2 of orthologous genes P21 … P2k

… … … …

Support value vector for a set #m of orthologous genes Pn1 … Pnk

Number of bipartitions (k) for N genomes is equal to 2(N-1)-N-1.

Page 4: A Web Interface to analyse SOM of   Bipartitions of Gene Phylogenies - A Walk Through

Visualizing Multiple Genomes: SOMs

SOM Self-Organizing Map An artificial neural network approach to clustering

we are looking for clusters of genes which favor certain tree topologies

Advantages over other clustering approaches: No a priori knowledge of how many clusters to expect Explicit summary of commonalities and differences between

clusters Visually appealing representation

T. Kohonen, Self-organizing maps, 3rd ed. Berlin ; New York: Springer, 2001.

Page 5: A Web Interface to analyse SOM of   Bipartitions of Gene Phylogenies - A Walk Through
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All clusters selected => ATV tree viewer applet (Zmasek & Eddy, Bioinformatics, 17, 383-384 2001) displays plurality consensus of all gene families.

ATV allows to modify display

Page 11: A Web Interface to analyse SOM of   Bipartitions of Gene Phylogenies - A Walk Through

Select branch to place root

Select to re-root tree

Page 12: A Web Interface to analyse SOM of   Bipartitions of Gene Phylogenies - A Walk Through

Cren-

archaeotaE

uryarchaeota

Root

Page 13: A Web Interface to analyse SOM of   Bipartitions of Gene Phylogenies - A Walk Through
Page 14: A Web Interface to analyse SOM of   Bipartitions of Gene Phylogenies - A Walk Through

List of strongly supported bipartitions, including conflicts

Page 15: A Web Interface to analyse SOM of   Bipartitions of Gene Phylogenies - A Walk Through

click to open map as pdf

Page 16: A Web Interface to analyse SOM of   Bipartitions of Gene Phylogenies - A Walk Through

select clusters that support bipartition

“well behaved” gene families

Page 17: A Web Interface to analyse SOM of   Bipartitions of Gene Phylogenies - A Walk Through

gene families that group Archaeoglobus with Methanosarcina

Page 18: A Web Interface to analyse SOM of   Bipartitions of Gene Phylogenies - A Walk Through

prolyl-tRNA synthetase, a gene family that groups the Halobacteria with the

outgroup.

This gene was acquired by the halobacterial lineage from the bacteria. These rare inter-domain gene transfers allow to correlate evolution in the three domains of life. (see Huang & Gogarten: Ancient horizontal gene transfer can benefit phylogenetic reconstruction. Trends in Genetics 22 (7): 361-366. 2006)