Transcript EdinburghBANG

GenBank
Huge amounts of data, easily accessible
Rate of growth of phylogenetic knowledge
7000
Cumulative number
6000
5000
4000
Number of papers
with “molecular”
and “phylogeny” in
Web of Science
3000
Number of
studies in
TreeBASE
2000
1000
0
1975
1980
1985
1990
Year
1995
2000
2005
Why have a phylogeny database?
• Archive data and trees (repeat old analyses with
new tools)
• Synthesize new data sets and trees (supermatrices
and supertrees)
• Big scale questions (tree shape, bias in tree
building methods, stability of trees over time)
• Hypothesis testing : find all phylogenies for taxa
with members in Gondwana -- do they show
similar area cladograms, amounts of sequence
divergence, etc.
• Who knows…(we won’t know until we try)
Obstacles in the way
• Ontologies (consistent names for organisms, genes, and
other kinds of data)
• How to store and query trees (what kind of queries do we
want?)
• Summarising information in trees (supertrees) and matrices
(supermatrices)
• Visualising very big trees
Peruvian Diving-petrel
(or, what’s in a name?)
• ITIS
Pelecanoides garnotii
• NCBI
Pelecanoides garnoti
• TreeBASE Pelecanoides garnoti AF076073
TreeBASE Names Project
http://darwin.zoology.gla.ac.uk/~rpage/TreeBASE/
• Aim is to map every name in TreeBASE
onto a valid taxonomic name (i.e., a name in
a database, or in the literature)
• Use exact-, substring-, and approximate
string matching (+ BLAST)
• So far 26819 out of 35084 names mapped
Hemideina maori (weta)
18 TreeBASE names = 1 real name
catodon
catadon
macrocephalus
3 TreeBASE names = 1 real name
Physeter catodon (Sperm Whale)
The case of the Harp seal
TreeBASE and GenBank have harp seals under two different
names, only ITIS knows that they are the same thing
• There are known knowns, things we know that
we know
• There are known unknowns, things we now
know we don’t know
• But there are also unknown unknowns, things we
do not know we don't know
Why taxonomy matters
(or
vs.
)
Searching on “Aves” in TreeBASE
finds 4 studies with birds…
•
Study #1: Gauthier, J., A.G. Kluge, and T.
Rowe. 1988. Amniote phylogeny and the
importance of fossils.
•
Study #2: Harshman, J., C. J. Huddleston,
J. P. Bollback, T. J. Parsons, and M. J.
Braun. 2003 inpress. True and False
Gavials: A Nuclear Gene Phylogeny of
Crocodylia.
•
Hedges, S. B., K. D. Moberg, and L. R.
Maxson.1990. Tetrapod phylogeny
inferred from 18s and 28s ribosomal
RNA sequences and a review of the
evidence for amniote relationships.
•
van Dijk, M. A. M., E. Paradis, F.
Catzeflis, and W. de Jong. 1999. The
virtues of gaps: Xenarthran (Edentate)
monophyly supported by a unique
deletion in alphaA-crystallin.
…but there are other birds in
TreeBASE!
Tree space in TreeBASE (overlap = 1)
There are 24 bird studies in TreeBASE,
but “tree surfing” won’t find them
Arabidopsis
rbcL
Fig. 1. The `data availability matrix' for green plant protein sequences from GenBank (release 132). A set of 130304 sequences for 14667 species
sequences were clustered into 61117 groups of homologous proteins by a combination of BLAST and single-linkage clustering (using the
program Blastclust from the NCBI Blast toolkit: http://www.ncbi.nlm.nih.gov/BLAST/ ). A column represents a protein or protein family; a row
represents one of the species in the dataset; and a dot indicates the existence of a sequence for that species and protein. Species are sorted
vertically by their number of sequences; the most-represented species ( Arabidopsis thaliana ) is at the top. Proteins are sorted horizontally by
the number of taxa for which they have been sequenced; the most heavily sequenced gene ( rbcL ) is on the right. This figure shows the most
heavily sampled corner of the data availability matrix; the remainder of the matrix is even more sparse.
Seeing the tree
(best seen when printed on 1.5 m wide paper…)
http://darwin.zoology.gla.ac.uk/~rpage/MyToL/www
Demo 1
QuickTime™ and a
BMP decompressor
are needed to see this picture.
Demo 2
QuickTime™ and a
Microsoft Video 1 decompressor
are needed to see this picture.
Comparing
classifications
for Psocoptera
NCBI (GenBank)
9 species
Lienhard & Smithers (2002)
[courtesy of Kevin Johnson]
4363 species
Bioinformatics envy - GenBank should NOT be our role model
www.biomoby.org
www.gmod.org
From journal to database…
Problem: not enough data and trees in journals make it into databases
7000
Cumulative number
6000
5000
4000
3000
2000
1000
0
1975
1980
1985
1990
Year
1995
2000
2005
Elsevier’s journal Molecular
Phylogenetics and Evolution is a
criminal waste of our efforts
Text, data, trees locked up in paper and PDF
… the database is the journal
1. Data + trees go into database
2. Text (annotation) added
3. Automatically generate a report
summarising the results
4. The report is the publication (can have a
DOI)
5. Open Access data and text
“Oh, the vision thing” George Bush (snr), 1987