Thank you everyone for your answers and suggestions. Here are the replies I got.
Best;
Omur
******
For topology reconstruction, Takezaki & Nei (1996) suggest that in both the
Infinite
Allele Model (IAM) and Stepwise Mutation Model (SMM), Cavalli-Sforza and Edwards
(1967)
chord distance and Nei et al. s (1983) genetic distance are preferably chosen,
while for
estimating branch lengths, (d�)� may yield better results. I attached Takezaki
& Nei's
paper to this email for you.
With the fitch-margoliash algorithm, implemented in FITCH in PHYLIP, you can
construct
such a hybrid tree, using e.g. Nei's genetic distance for topology and delte mu
2 for
branch lengths.
I used to calculate delta mu 2 values in MSA.
Dieter.Anseeuw@kuleuven-kortrijk.be
Unless your individuals are all of different species they don't have a
"phylogenetic relationsip". Instead each locus has a different coalescent
tree. By forcing them all to have the same tree you are distorting the
relationships.
You should look into programs like Migrate or IM. If you're thinking in
terms of phylogenies of individuals you should re-think the matter.
J.F.
----
Joe Felsenstein joe@gs.washington.edu
Department of Genome Sciences and Department of Biology,
University of Washington, Box 357730, Seattle, WA 98195-7730 USA
Depending on your sample size, you many be able to use more appropriate methods
for
determining the relationships between populations. Phylogenetic methods were
developed
for reciprocally monophyletic species and should really not be applied to
populations
that exchange genes. There are now some better methods to determine the
relationships
among populations. Two packages that I have found quite useful are Structure
(http://pritch.bsd.uchicago.edu/ structure.html) and Population Graph
(http://dyerlab.bio.vcu.edu/ wiki/index.php/Software).
David B Lowry <dbl2@duke.edu>
delta mu square values can (as far as I know) only be calculated with RSTCALC.
There are
however other ways to conduct a phylogenetic analysis based on allele frequency
data,
e.g. Nei's genetic distance.
I am attaching a protocol I wrote for doing so. It involves the following
softwares
"Convert", "Phylip" and "Treeview". All are available for free.
______
Dr. Susanne Hauswaldt
Unit of Evolutionary Biology and Systematics
Department of Biological Sciences
University of Potsdam
here's a list of programs that compute genetic distances from microsatellite
data as
well as a distance tree. Some even boostrap across loci.
The best known program for microsatellite distances is MICROSAT:
http://hpgl.stanford.edu/projects/microsat
Microsatellite Analyzer or MSA (does all kinds of distances, among other
things):
http://i122server.vu-wien.ac.at/MSA/info.html/ MSA_info.html#distance
Populations: http://bioinformatics.org/project/?group_id=84
POPTREE (just to make the NJ tree): http://www.bio.psu.edu/People/
Faculty/Nei/Lab/software.htm
SHAREDST (across individuals): http://www2.biology.ualberta.ca/
jbrzusto/sharedst.php
GeneDist (across populations): http://www2.biology.ualberta.ca/
jbrzusto/GeneDist.php
Sergios-Orestis Kolokotronis
Dept. of Ecology, Evolution, and Environmental Biology
Columbia University
sk2059@columbia.edu
Try the AFC plots in the GENETIX (Belkir et al.) software. The plots are not
based on delta-mu ^2, they partition variance instead. Yet, each individual
will be represented in a multi-vector space.
scott
_________
Scott M. Blankenship Ph. D.
Biologist/Geneticist
Washington Department Fish and Wildlife
blanksmb@dfw.wa.gov
********
In the analysis of microsatellite loci, if the number of loci
examined is small, Da or chord distance should work better than delta myu
square to estimate the phylogenetic relationship of populations.
Previously, we have studied the probability of obtaining a correct
tree by using Da, chord distance, delta myu square, and some other distances
for microsatellite loci and showed that Da and chord distance work better
than delta myu square unless hundreds of loci are used (Takezaki and Nei
1996). This is because even though the value of delta myu square is expected
to increase linearly with time under the stepwise mutation model that the
microsatellite loci roughly follow, the sampling error of the delta myu
square is used.
More explanations about genetic distance and phylogenetic tree are
found in chapter 13 of the book of Nei and Kumar (2000). In this chapter,
the example of the phylogenetic trees constructed from 25 microsatellite
loci of human populations is shown. The tree constructed using Da distance
looks reasonable. However, even with the use of 25 loci, in the tree made
with delta myu square populations from the same geographic region does not
form clusters.
Da distance can be computed and used for constructing the
phylogenetic tree with neighbor-joining method or UPGMA by a computer
program DISPAN and POPTREE. POPTREE can also compute delta myu square for
constructing phylogenetic trees.
DISPAN and POPTREE are available at the following webpage.
http://www.bio.psu.edu/People/Faculty/Nei/Lab/software.htm
References
Takezaki, N. and M. Nei. 1996. Genetics 144: 389-399.
Nei, M. and S. Kumar. 2000. Molecular Evolution and Phylogenetics. Oxford
University Press, New York.
Best regards,
--------
Naoko Takezaki
Information Technology Center, Kagawa University
1750-1 Ikenobe, Mikicho, Kitagun, Kagawa 761-0793
Japan
TEL/FAX 087-891-2419
email: takezaki@med.kagawa-u.ac.jp
******************
Omur Kayikci
Associate in Research
Magwene Lab
DCMB Group, LSRC B232
Duke University
Omur Kayikci <kayikci@duke.edu>