Table of Contents
Arlequin
Arlequin ver 3.5 (released 24 February 2010)
The goal of Arlequin is to provide the average user in population genetics with quite a large set of basic methods and statistical tests, in order to extract information on genetic and demographic features of a collection of population samples.
The analyses Arlequin can perform on the data fall into two main categories: intra-population and inter-population methods.
Computes indices of genetic diversity, F-statistics and genetic distances between populations; exact test of HWE, LD and population differentiation; tests selective neutrality within populations; Mantel test; estimates gametic phase from multilocus genotypes; estimated demographic parameters form mismatch distribution
Program information
- program written in C++
- Windows version (XP, Vista, 7)
- LINUX
Data type handled
- DNA sequences
- RFLP
- SNP
- Microsattelite
- Standard data
- Allele frequency data
In haplotypic form:
- haplotypes (i.e. combination of alleles at one or more loci)
- haploid/diploid
in genotypic form:
- genotypes
- diploid
- known/unknown gametic phase
- recessive/no recessive alleles
Input Files
Contain the description of the properties of the data, as well as the raw data themselves. The input files should have a “*.arp” extension (for ARlequin Project).
structured into two main sections:
- Profile section (mandatory)
- Data section (mandatory):
- Haplotype list (optional)
- Distance matrices (optional)
- Samples (mandatory)
- Genetic structure (optional)
- Mantel tests (optional)
example:
The following small example is a project file containing four populations. The data type is STANDARD genotypic data with unknown gametic phase:
[Profile] Title="Fake HLA data" NbSamples=4 GenotypicData=1 GameticPhase=0 DataType=STANDARD LocusSeparator=WHITESPACE MissingData='?' [Data] [[Samples]] SampleName="A sample of 6 Algerians" SampleSize=6 SampleData={ 1 1 1104 0200 0700 0301 3 3 0302 0200 1310 0402 4 2 0402 0602 1502 0602 } SampleName="A sample of 11 Bulgarians" SampleSize=11 SampleData={ 1 1 1103 0301 0301 0200 2 4 1101 0301 0700 0200 3 1 1500 0502 0301 0200 4 1 1103 0301 1202 0301 5 1 0301 0200 1500 0601 6 3 1600 0502 1301 0603 } SampleName="A sample of 12 Egyptians" SampleSize=12 SampleData={ 1 2 1104 0301 1600 0502 3 1 1303 0301 1101 0502 4 3 1502 0601 1500 0602 6 1 1101 0301 1101 0301 8 4 1302 0502 1101 0609 9 1 1500 0302 0402 0602 } SampleName="A sample of 8 French" SampleSize=8 SampleData={ 219 1 0301 0200 0101 0501 239 2 0301 0200 0301 0200 249 1 1302 0604 1500 0602 250 3 1401 0503 1301 0603 254 1 1302 0604 } [[Structure]] StructureName="My population structure" NbGroups=2 Group={ "A sample of 6 Algerians" "A sample of 12 Egyptians" } Group={ "A sample of 11 Bulgarians" "A sample of 8 French" }
Profile section:
- Title (string within “”):
Title=”title xy”
- Number of samples (int 1-1000):
NbSamples =3
- Type of data (DNA, RFLP, MICROSAT, STANDARD, FREQUENCY):
DataType = DNA
- Haplotypic/genotypic data (0/1):
GenotypicData = 0
- Optionally (default value):
- locus separator (WHITESPACE, TAB, NONE, …):
LocusSeparator = TAB
- gametic phase known/unknown (1/0):
GameticPhase = 1
- recessive/ co-dominant allele (1/0):
RecessiveData = 1
- code for recessive allele (string within “null”):
RecessiveAllel =”xxx”
- code for missing data (character within “?” or ‘?’):
MissingData = ‘$’
- frequencies as absolute/relative values (ABS/REL):
Frequency = ABS
- significant digits for haplotype frequency outputs (real number 1e-2 – 1e-7(1e-5)):
FrequencyThreshold = 0.00001
- convergence criterion for the EM algorithm (real number 1e-7 – 1e-12):
EpsilonValue = 1e-10
Data section:
Haplotype list (optional):
define list of haplotypes (intern or extern)
- intern:
[[HaplotypeDefinition]] #start the section of Haplotype definition HaplListName="list1" #give any name you whish to this list HaplList={ h1 A T #on each line, the name of the haplotype is h2 G C # followed by its definition. h3 A G h4 A A h5 G G }
- extern:
[[HaplotypeDefinition]] #start the section of Haplotype definition HaplListName="list1" #give any name you whish to this list HaplList = EXTERN "hapl_file.hap"
Distance matrix (optional):
matrix of genetic distances between haplotypes can be specified (intern or extern)
- intern:
[[DistanceMatrix]] #start the distance matrix definition section MatrixName= "none" # name of the distance matrix MatrixSize= 4 # size = number of lines of the distance matrix MatrixData={ h1 h2 h3 h4 # labels of the distance matrix (identifier of the 0.00000 # haplotypes) 2.00000 0.00000 1.00000 2.00000 0.00000 1.00000 2.00000 1.00000 0.00000 }
- extern:
[[DistanceMatrix]] #start the distance matrix definition section MatrixName= "none" # name of the distance matrix MatrixSize= 4 # size = number of lines of the distance matrix MatrixData= EXTERN "mat_file.dis"
Samples (obligatory):
Defines haplotypic/genotypic content of the different samples
- name for each sample (string within “”):
SampleName = “name xy”
- size of sample (int value):
SampleSize = 732
- data itself (list of haplotypes or genotypes and their frequencies, entered with braces):
[[Samples]] #start the samples definition section SampleData={ id1 1 ACGGTGTCGA id2 2 ACGGTGTCAG id3 8 ACGGTGCCAA id4 10 ACAGTGTCAA id5 1 GCGGTGTCAA }
frequency data:
SampleData={ id1 1 id2 2 id3 8 id4 10 id5 1 }
- haplotypic data: for each haplotype its identifier and sample frequency (no haplotype list has been defined: also allelic content of the haplotype)
- genotypic data: for each genotype its identifier, sample frequency, allelic content (on two separate lines). As list of genotypes or list of individuals.
Id1 2 ACTCGGGTTCGCGCGC # the first pseudo-haplotype ACTCGGGCTCACGCGC # the second pseudo-haplotype
or
my_id 4 0 0 1 1 0 1 0 1 0 0 1 1
Genetic structure (only required for AMOVA):
specifies the hierarchical genetic structure of the samples. It is possible to define groups of populations.
- start of the subsection:
[[Structure]]
- name for the genetic structure (string within “”):
StructureName = “A example”
- number of groups defined in the structure (int value):
NbGroups = 5
- group definitions (list containing the names of the samples belonging to the group, entered within braces):
NbGroups=2 Group ={ population1 population2 population3 } Group ={ population4 population5 }
Mantel test settings
allows to specify some distance matrices. The goal is to compute a correlation between the Ymatrix and X1 or a partial correlation between the Ymatrix, X1 and X2. The Ymatrix can be either a pairwise population FST matrix or a custom matrix entered into the project by the user. X1 (and X2) have to be defined in the project.
- start of the subsection:
[[Mantel]]
- size of the matrices (pos. int value):
MatrixSize= 5
- number of matrices among which we compute the correlations (2/3):
MatrixNumber= 2
- matrix that is used as genetic distance (“fst” (→Y=Fst)/ “log_fst” (→Y=log(Fst))/ “slatkinlinearfst” (→Y=Fst/(1-Fst))/ “log_slatkinlinearfst” (→Y=log(Fst/(1-Fst)))/ “nm” (→Y=(1-Fst)/(2 Fst))/ “custom” (→Y= user-specified in the project)):
YMatrix = “fst”
- labels that identify the columns of the YMatrix (list containing the names of the lable name belonging to the group, entered within braces):
YMatrixLabels = { "Population1 " "Population4" "Population2" "Population8" "Population5" }
- keyword that allows to define a matrix with witch the correlation with the YMatrix is computed:
DistMatMantel={ 0.00 3.20 0.00 0.47 0.76 0.00 0.00 1.23 0.37 0.00 0.22 0.37 0.21 0.38 0.00 }
- Labels defining the sub-matrix on witch the correlation is computed:
UsedYMatrixLabels={ "Population1 " "Population5" "Population8" }
How to cite
Excoffier, L. and H.E. L. Lischer (2010) Arlequin suite ver 3.5: A new series of programs to perform population genetics analyses under Linux and Windows. Molecular Ecology Resources. 10: 564-567.