
Department of Ecology & Evolution,
Biology Building, UNIL, CH1015 LAUSANNE, Switzerland
Tel :+41(0)21 692 4160 (sec) ; Fax:+41(0)21 692 4265



A software developed by Jérôme
Goudet.
FSTAT is a computer package for PCs which estimates and tests gene diversities
and differentiation statistics from codominant genetic markers. It computes
both Nei and Weir & Cockerham families of estimators of gene diversities
and Fstatistics, and tests them using randomisation methods. The current
version (Feb. 2002) is 2.9.3.2. Previous versions are not maintained
anymore. However, if you still run DOS, you can still download the old
version (1.2) below.
To install FSTAT 2.9.3, double click the file fstat293dist.exe once you
have downloaded it. This will create under the folder you have chosen
the following architecture of folders and files:
Fstat293.exe
Fstat293.hlp
Fstat293.cnt
Readme.txt
Readme.doc
In order to read the help file, you will need to install winhlp32.exe
The following folders contain data and example files, use of which is
detailed in the help file:
.\data
.\data\bias dispersal
.\data\multiple regression
What FSTAT does
From a data set of codominant or haploid genetic markers, FSTAT calculates
the following:
 Number of individuals per sample and loci.
 Allele frequency estimated per sample and overall.
 Observed and expected number of each genotype per sample and locus.
 Unbiased gene diversity per sample and locus.
 Number of alleles sampled per locus and sample, as well as overall.
 [NEW] Allelic richness per locus and sample, as well as overall samples
 Fis per locus and sample, as well as a test of whether it is significantly
positive or negative (significant deficit and excess of heterozygotes
respectively).
 Nei's (1987) estimators of gene diversities and differentiation.
 Weir & Cockerham (1984) Capf (Fit), theta (Fst) and smallf (Fis) estimated
per allele, per locus and overall. FSTAT also calculates Hamilton's (1971)
relatedness relat=2Fst/(1+Fit), calculated using an estimator strictly
equivalent to Queller and Goodnight's (1989). This measure is the average
relatedness of individuals within samples when compared to the whole data
set.
Confidence intervals based on resampling schemes are provided for Weir
& Cockerham statistics:
 Jackknifing per locus over samples is performed. The resampling unit
are the different samples. This procedure is only carried out if there
are more than 4 samples.
 Jackknifing over loci. In this case, the resampling units are the different
loci. This procedure is only carried out if there are more than 4 loci.
 Bootstrapping over loci. Bootstrapping over loci is performed only when
there is more than 4 loci in the data set.
 Estimation of R statistics (Slatkin, 1995), specifically designed for
microsatellite undergoing stepwise mutations.
 Estimation of Fst (theta) per pair of samples.
 Overall test whether each sample at each locus is in HW equilibrium.
 Test whether the entire data set is in HW equilibrium.
 Test whether samples are differentiated assuming either that there is
HW within samples or that there is not (Only one of these 2 tests can
be carried out).
 Test whether each sample at each locus is in HardyWeinberg (HW) equilibrium.
 Test whether each pair of samples is differentiated. The tests do not
assume random mating within samples. A table of significant pairwise differentiation
after corrections for multiple testing is produced.
 [NEW] Test whether each pair of loci in each sample and overall is at
genotypic equilibrium
 [NEW] Test whether groups of samples differ for a large panel of statistics
 [NEW] Test whether categories of individuals differ in dispersal rates
(four different tests)
 [NEW] Convert FSTAT format to GENEPOP and vice versa
 [NEW] Performs multiple regression or Partial Mantel tests
Download FSTAT

