Arlequin User Manual
Contents
1. ARLEQUIN A software for population genetic data analysis Copyright 1995 99 L Excotfier ver 1 1 Manual Arlequin ver 1 1 ARLEQUIN ver 1 1 A software for population genetic data analysis Authors Stefan Schneider Jean Marc Kueffer David Roessli and Laurent Excoffier Genetics and Biometry Laboratory Dept of Anthropology and Ecology University of Geneva CP 511 1211 Geneva 24 Switzerland E mail arlequin sc2a unige ch URL http anthropologie unige ch arlequin December 1997 Manual Arlequin ver 1 1 Table of contents Table of contents 1 Introduction 1 1 Why Arlequin 1 2 Arlequin philosophy 1 3 About this manual 1 4 Data types handled by Arlequin 1 4 1 DNA sequences 1 4 2 RFLP Data 1 4 3 Microsatellite data 1 4 4 Standard data 1 4 5 Allele frequency data 1 5 Methods implemented in Arlequin 1 6 System requirements 1 7 Installing and uninstalling Arlequin 1 8 List of files included in the Arlequin package 1 9 Arlequin limitations 1 10 How to cite Arlequin 1 11 Acknowledgements 1 12 Bug report and comments 1 13 How to get the last version of the Arlequin software 1 14 What is new in version 1 1 compared to version 1 0 1 15 Forthcoming developments 1 16 Remaining problem 2 Getting started 2 1 Preparing input files 2 2 Loading project files into Arlequin 2 3 Selecting analyses to be performed on your data 2 4 Creating and using Setting Files 2 5 Performing the analyses 2 6 Sto2. the same types of analyses irrespective of the format of the data Because Arlequin has a rich set of features and many options it means that the user has to spend some time in learning them However we hope that the learning curve will not be that steep Arlequin is made available free of charge as long as we have enough local resources to support the development of the program 1 3 About this manual The main purpose of this manual is to allow you to use Arlequin on your own in order to limit as far as possible e mail exchange with us In this manual we have tried to provide a description of 1 the data types handled by Arlequin 2 the way these data should be formatted before the analyses 3 the graphical interface 4 the impact of different options on the computations 5 methodological outlines describing which computations are actually performed by Arlequin Even though this manual contains the description of some theoretical aspects it should not be considered as a textbook in basic population genetics We strongly recommend you to consult the original references provided with the description of a given method if you are in doubt with any aspect of the analysis Manual Arlequin ver 1 1 Introduction 7 1 4 Data types handled by Arlequin Arlequin can handle several types of data either in haplotypic or genotypic form The basic data types are e DNA sequences e RFLP data e Microsatellite data e Standard data e
3. 60 60 61 61 61 61 62 62 64 64 65 66 66 66 67 67 67 67 69 70 70 71 72 72 73 73 75 76 76 79 Manual Arlequin ver 1 1 Introduction 6 1 INTRODUCTION 1 1 Why Arlequin Arlequin is the French translation of Arlecchino a famous character of the Italian Commedia dell Arte As a character he has many aspects but he has the ability to switch among them very easily according to its needs and to necessities This polymorphic ability is symbolized by his colorful costume from which the Arlequin icon was designed 1 2 Arlequin philosophy The goal of Arlequin is to provide the average user in population genetics with quite a large set of methods and statistical tests in order to extract information on genetic and demographic features of a collection of population samples The graphical interface has been designed such as to allow the user to rapidly select the different analyses he wants to perform on his data We felt important to be able to explore the data to analyze several times the same data set from different perspectives with different selected options The statistical tests implemented in Arlequin have been chosen such as to minimize hidden assumptions and to be as powerful as possible Thus they often take the form of either permutation tests or exact tests with some exceptions Finally we wanted Arlequin to be able to handle genetic data under many different forms and to try to carry out
4. TAB NONE or any character other than or the character specifying missing data Default WHITESPACE GameticPhase Specifies if the gametic phase is 0 gametic phase not known known for genotypic data 1 known gametic phase only Default 1 RecessiveData Specifies whether recessive 0 co dominant data alleles are present at all loci for 1 recessive data genotypic data Default 0 RecessiveAllele Specifies the code for the Any string within quotation marks recessive allele This string can be explicitly used in the input file to indicate the occurrence of a recessive homozygote at one or several loci Default null MissingData A character used to specify the or any character within quotes other than those code for missing data previously used Default Frequency Specifies the format of ABS absolute values haplotype frequencies REL relative values absolute values will be found by multiplying the relative frequencies by the sample sizes Default ABS Manual Arlequin ver 1 1 Appendix 77 CompDistMatrix Specifies if the distance matrix O use any specified distance matrix has to be computed from the data FrequencyThreshold The minimum frequency a 1 compute distance matrix from haplotypic information Default 0 A real number between 1e 2 and le 7 haplotype has to reach for being Default 1e 5 listed in any output file EpsilonValue The EM algorithm A real number between l
5. the Bootstrap and other Resampling Plans Regional Conference Series in Applied Mathematics Philadelphia Ewens W J 1972 The sampling theory of selectively neutral alleles Theor Popul Biol 3 87 112 Ewens W J 1977 Population genetics theory in relation to the neutralist selectionist controversy In Advances in human genetics edited by Harris H and Hirschhorn K New York Plenum Press p 67 134 Excoffier L Smouse P and Quattro J 1992 Analysis of molecular variance inferred from metric distances among DNA haplotypes Application to human mitochondrial DNA restriction data Genetics 131 479 491 Excoffier L and M Slatkin 1995 Maximum likelihood estimation of molecular haplotype frequencies in a diploid population Mol Biol Evol 12 921 927 Excoffier L and M Slatkin 1998 Incorporating genotypes of relatives into a test of linkage disequilibrium Am J Hum Genet January issue Goudet J M Raymond T de Meeiis and F Rousset 1996 Testing differentiation in diploid populations Genetics 144 1933 1940 Guo S and Thompson E 1992 Performing the exact test of Hardy Weinberg proportion for multiple alleles Biometrics 48 361 372 Harpending R C 1994 Signature of ancient population growth in a low resolution mitochondrial DNA mismatch distribution Hum Biol 66 591 600 Manual Arlequin ver 1 1 References 80 Hudson R R 1990 Gene genealogies and the coalescent proces pp 1 44 in Oxford S
6. transversion and G C content biases Mol Biol Evol 9 678 687 Tamura K and M Nei 1993 Estimation of the number of nucleotide substitutions in the control region of mitochondrial DNA in humans and chimpanzees Mol Biol Evol 10 512 526 Uzell T and K W Corbin 1971 Fitting discrete probability distribution to evolutionary events Science 172 1089 1096 Watterson G 1975 On the number of segregating sites in genetical models without recombination Theor Popul Biol 7 256 276 Watterson G 1978 The homozygosity test of neutrality Genetics 88 405 417 Watterson G A 1986 The homozygosity test after a change in population size genetics 112 899 907 Weir B S 1996 Genetic Data Analysis II Methods for Discrete Population Genetic Data Sinauer Assoc Inc Sunderland MA USA Manual Arlequin ver 1 1 References 82 Weir B S and Cockerham C C 1984 Estimating F statistics for the analysis of population structure Evolution 38 1358 1370 Wright S 1951 The genetical structure of populations Ann Eugen 15 323 354 Wright S 1965 The interpretation of population structure by F statistics with special regard to systems of mating Evol 19 395 420 Zouros E 1979 Mutation rates population sizes and amounts of electrophoretic variation of enzyme loci in natural populations Genetics 92 623 646
7. 2 Diversity indices 6 4 3 Neutrality tests 6 4 4 Gametic disequilibrium 6 4 5 Genetic structure 6 4 6 Launch Pad 7 Methodological outlines 7 1 Intra population level methods 7 1 1 Standard diversity indices 7 1 1 1 Gene diversity 7 1 1 2 Number of usable loci 7 1 1 3 Number of polymorphic sites S 7 1 2 Molecular indices 7 1 2 1 Mean number of pairwise differences 7 7 1 2 2 Nucleotide diversity or average gene diversity over L loci RFLP and DNA data 7 1 2 3 Theta estimators 7 1 2 3 1 Theta Hom 7 1 2 3 2 Theta S 7 1 2 3 3 Theta k 7 1 2 3 4 Theta 7 7 1 2 4 Mismatch distribution 7 1 2 5 Estimation of genetic distances between DNA sequences 7 1 2 5 1 Pairwise difference 28 28 29 29 29 30 30 30 31 32 33 34 35 35 35 35 35 37 37 37 38 38 39 39 39 41 43 44 46 48 50 5I 51 51 51 51 51 51 52 52 53 53 54 54 55 56 Manual Arlequin ver 1 1 Table of contents 7 1 2 5 2 Percentage difference 7 1 2 5 3 Jukes and Cantor 7 1 2 5 4 Kimura 2 parameters 7 1 2 5 5 Tamura 7 1 2 5 6 Tajima and Nei 7 1 2 5 7 Tamura and Nei 7 1 2 6 Estimation of genetic distances between RFLP haplotypes 7 1 2 6 1 Number of pairwise difference 7 1 2 6 2 Proportion of difference 7 1 2 7 Estimation of distances between Microsatellite haplotypes 7 1 2 7 1 No of different alleles 7 1 2 7 2 Sum of squared size difference 7 1 2 8 Estimation of distances between Standard haplotypes 7 1 2 8 1 Number of pairwise differen
8. Allele frequency data By haplotypic form we mean that genetic data can be presented under the form of haplotypes i e a combination of alleles at one or more loci This haplotypic form can result from the analyses of haploid genomes mtDNA Y chromosome prokaryotes or from diploid genomes where the gametic phase could be inferred by one way or another Note that allelic data are treated here as a single locus haplotype Ex 1 haplotypic RFLP data 100110100101001010 Ex 2 haplotypic standard HLA data DRB1 0101 DQB1 0102 DPB1 0201 By genotypic form we mean that genetic data is presented under the form of diploid genotypes i e a combination of pairs of alleles at one or more loci Exl genotypic DNA sequence data ACGGCA AAGCATGACATACGGATTGACA ACGGGA TAGCATGACATTCGGATAGACA Ex 2 genotypic Microsatellite data 63 24 32 62 24 30 The gametic phase of a multi locus genotype may be either known or unknown If the gametic phase is known the genotype can be considered as made up of two well defined haplotypes For genotypic data with unknown gametic phase you can consider the two alleles present at each locus as codominant or you can allow for the presence of a recessive allele This gives finally four possible forms of genetic data e Haplotypic data e Genotypic data with known gametic phase e Genotypic data with unknown gametic phase no recessive alleles e Genotypic data with unknown gametic ph
9. account for genotypic data 1 the component of variance due to differences only between haplotypes within individuals and its associated statistics will be computed Group The definition of a group of A series of strings within quotation marks all samples identified by their enclosed within braces and if desired on separate SampleName listed within lines braces Manual Arlequin ver 1 1 References 79 9 REFERENCES Abramovitz M and I A Stegun 1970 Handbook of Mathematical Functions Dover New York Aris Brosou S and L Excoffier 1996 The impact of population expansion and mutation rate heterogeneity on DNA sequence polymorphism Mol Biol Evol 13 494 504 Cavalli Sforza L L and W F Bodmer 1971 The Genetics of Human Populations W H Freeman and Co San Francisco CA Chakraborty R 1990 Mitochondrial DNA polymorphism reveals hidden heterogeneity within some Asian populations Am J Hum Genet 47 87 94 Chakraborty R and K M Weiss 1991 Genetic variation of the mitochondrial DNA genome in American Indians is at mutation drift equilibrium Am J Hum Genet 86 497 506 Cockerham C C 1969 Variance of gene frequencies Evolution 23 72 83 Cockerham C C 1973 Analysis of gene frequencies Genetics 74 679 700 Dempster A N Laird and D Rubin 1977 Maximum likelihood estimation from incomplete data via the EM algorithm J Roy Statist Soc 39 1 38 Efron B 1982 The Jacknife
10. ase recessive alleles Manual Arlequin ver 1 1 Introduction 8 1 4 1 DNA sequences DNA sequences of arbitrary length can be accommodated by Arlequin Each nucleotide is considered as a distinct locus The four nucleotides C T A G are considered as unambiguous alleles for each locus and the is used to indicate a deleted nucleotide Usually the question mark codes for an unknown nucleotide The following notation for ambiguous nucleotides are also recognized R A G purine Y C T pyrimidine M A C W A T S C G K G T B C G T D A G T H A C T V A C G N A C G T 1 4 2 RFLP Data RFLP haplotypes of arbitrary length can be handled by Arlequin Each restriction site is considered as a distinct locus The presence of a restriction site should be coded as a 1 and its absence as a 0 The character should be used to denote the deletion of a site not its absence due to a point mutation 1 4 3 Microsatellite data The raw data consist here of the allelic state of one or an arbitrary number of microsatellite loci For each locus one should in principle provide the number of repeats of the microsatellite motif as the allelic definition if one wants his data to be analyzed according to the step wise mutation model for the analysis of genetic structure It may occur that the absolute number of repeats is unknown If the difference in length between amplified products is the direct consequence of cha
11. ces 7 1 3 Haplotype frequency estimation 7 1 3 1 Haplotypic data or Genotypic data with known Gametic phase 7 1 3 2 Genotypic data with unknown Gametic phase 7 1 4 Linkage disequilibrium between pairs of loci 7 1 4 1 Exact test of linkage disequilibrium haplotypic data 7 1 4 2 Likelihood ratio test of linkage disequilibrium genotypic data gametic phase unknown 7 1 4 3 Measures of gametic disequilibrium haplotypic data 7 1 5 Hardy Weinberg equilibrium 7 1 6 Neutrality tests 7 1 6 1 Ewens Watterson homozygosity test 7 1 6 2 Ewens Watterson Slatkin exact test 7 1 6 3 Chakraborty s test of population amalgamation 7 1 6 4 Tajima s test of selective neutrality 7 2 Inter population level methods 7 2 1 Population genetic structure inferred by analysis of variance AMOVA 7 2 1 1 Haplotypic data one group of populations 7 2 1 2 Haplotypic data several groups of populations 7 2 1 3 Genotypic data one group of populations no within individual level 7 2 1 4 Genotypic data several groups of populations no within individual level 7 2 1 5 Genotypic data one population within individual level 7 2 1 6 Genotypic data one group of populations within individual level 7 2 1 7 Genotypic data several groups of populations within individual level 7 2 2 Population pairwise genetic distances 7 2 3 Exact tests of population differentiation 8 Appendix 8 1 Overview of input file keywords 9 References 56 56 57 57 58 58 59 59 60 60
12. e 7 and 1e 12 convergence criterion For Default 1e 7 advanced users only Keywords Description Possible values Data HaplotypeDefinition facultative section HaplListName The name of a haplotype A string within quotation marks definition list HaplList The list of haplotypes listed A series of haplotype definitions given on separate within braces lines for each haplotype Each haplotype is defined by a haplotype label and a combination of alleles at different loci The Keyword EXTERN followed by a string within quotation marks may be used to specify that a given haplotype list is in a different file Keywords Description Possible values Data DistanceMatrix facultative section MatrixName The name of the distance matrix A string within quotation marks MatrixSize The size of the matrix A positive integer larger than zero corresponding to the number of haplotypes listed in the haplotype list LabelPosition Specifies whether haplotypes ROW the haplotype labels will be entered labels are entered by row or by consecutively on one or several lines within the column MatrixData segment before the distance matrix elements COLUMN the haplotype labels will be entered as the first column of each row of the distance matrix itself MatrixData The matrix data itself listed The matrix data will be entered as a format free within braces lower diagonal matrix The haplotype labels can be either entered co
13. es 68 259 260 Slatkin M and Excoffier L 1996 Testing for linkage disequilibrium in genotypic data using the EM algorithm Heredity 76 377 383 Stewart F M 1977 Computer algorithm for obtaining a random set of allele frequencies for a locus in an equilibrium population Genetics 86 482 483 Strobeck K 1987 Average number of nucleotide differences in a sample from a single subpopulation A test for population subdivision Genetics 117 149 153 Tajima F 1983 Evolutionary relationship of DNA sequences in finite populations Genetics 105 437 460 Tajima F 1989a Statistical method for testing the neutral mutation hypothesis by DNA polymorphism Genetics 123 585 595 Tajima F 1989b The effect of change in population size on DNA polymorphism Genetics 123 597 601 Tajima F 1993 Measurement of DNA polymorphism In Mechanisms of Molecular Evolution Introduction to Molecular Paleopopulation Biology edited by Takahata N and Clark A G Tokyo Sunderland MA Japan Scientific Societies Press Sinauer Associates Inc p 37 59 Tajima F and Nei M 1984 Estimation of evolutionary distance between nucleotide sequences Mol Biol Evol 1 269 285 Tajima F 1996 The amount of DNA polymorphism maintained in a finite population when the neutral mutation rate varies among sites Genetics 143 1457 1465 Tamura K 1992 Estimation of the number of nucleotide substitutions when there are strong transition
14. nges in repeat numbers then the minimum length of the amplified product could serve as a reference allowing to code the other alleles in terms of additional repeats as compared to this reference If this strategy is impossible then any other number could be used as an allelic code but the step wise mutation model cold not be assumed for theses data 1 4 4 Standard data Data for which the molecular basis of the polymorphism is not particularly defined or when different alleles are considered as mutationally equidistant from each other Standard data haplotypes are thus compared for their content at each locus without taking special care about the nature of the alleles which can be either similar or different For instance HLA data human MHC enters the category of standard data Manual Arlequin ver 1 1 Appendix 76 8 APPENDIX 8 1 Overview of input file key words Keywords Description Possible values Profile Title A title describing the present A string of alphanumeric characters within double analysis quotes NbSamples The number of different A positive integer larger than zero samples listed in the data file DataType The type of data to be analyzed STANDARD only one type of data per DNA project file is allowed RFLP MICROSAT FREQUENCY GenotypicData Specifies if genotypic or 0 haplotypic data gametic data is available 1 genotypic data LocusSeparator The character used to separate WHITESPACE adjacent loci
15. nsecutively on one or several lines Gf LabelPosition ROW or entered at the first column of each row if labelPosition COLUMN The special keyword EXTERN may be used followed by a file name within quotation marks stating that the data must be read in an another file Manual Arlequin ver 1 1 Appendix 78 Keywords Description Possible values Data Samples SampleName The name of the sample This A string within quotation marks keyword is used to mark the beginning of a sample definition SampleSize Specifies the sample size An integer larger than zero For haplotypic data it must specify the number of gene copies in the sample For genotypic data it must specify the number of individuals in the sample SampleData The sample data listed within The keyword EXTERN may be used followed by braces a file name within quotation marks stating that the data must be read in a separate file The SampleData keyword ends a sample definition Keywords Description Possible values Data Structure facultative section StructureName The name of a given genetic A string of characters within quotation marks structure to test NbGroups The number of groups of An integer larger than zero populations IndividualLevel Specifies whether the level of 0 the component of variance due to differences genetic variability within between haplotypes within individuals will be individuals has to be taken into ignored
16. pping the computations 2 7 Consulting the results 3 Input files 3 1 Format of Arlequin input files 3 2 Project file structure 3 2 Profile section 3 2 2 Data section 3 2 2 1 Haplotype list optional 3 2 22 Distance matrix optional 3 2 2 3 Samples 3 2 2 4 Genetic structure 3 3 Eexample of an input file 3 4 Automatically creating the outline of a project file 3 5 Conversion of data files 3 6 Arlequin batch files 4 Output files 4 1 Result file ODO oo EO o OO NN DN OC oO A NN NNN NNN NNN A WH NH NH NHB NH CO SO NN NNN NON mM NAA ANH CA tA Un t b ND NN ND DD M NA AW O oO o0 1 NI to N Co Go Manual Arlequin ver 1 1 Table of contents 4 2 View your results in HTML browser 4 3 Arlequin Log file 4 4 Back up file 4 5 Linkage Disequilibrium Result File 4 6 Variance components null distribution histograms 5 Examples of input files 5 1 Example of allele frequency data 5 2 Example of standard data Genotypic data unknown gametic phase recessive alleles 5 3 Example of DNA sequence data Haplotypic 5 4 Example of microsatellite data Genotypic 5 5 Example of RFLP data Haplotypic 5 6 Example of standard data Genotypic data known gametic phase 6 Arlequin interface 6 1 Menus 6 1 1 File Menu 6 1 2 Edit Menu 6 1 3 Project Menu 6 1 4 Setup Menu 6 1 5 Special Menu 6 1 6 Window Menu 6 1 7 Help Menu 6 2 Toolbar 6 3 Status Bar 6 4 Dialog boxes 6 4 1 General Settings 6 4
17. rsity Press New York NY USA Raymond M and F Rousset 1994 GenePop ver 3 0 Institut des Sciences de l Evolution Universit de Montpellier France Raymond M and F Rousset 1995 An exact tes for population differentiation Evolution 49 1280 1283 Reynolds J Weir B S and Cockerham C C 1983 Estimation for the coancestry coefficient basis for a short term genetic distance Genetics 105 767 779 Rice J A 1995 Mathematical Statistics and Data Analysis 2nd ed Duxburry Press Belmont CA Rogers A 1995 Genetic evidence for a Pleistocene population explosion Evolution 49 608 615 Rogers A R and H Harpending 1992 Population growth makes waves in the distribution of pairwise genetic differences Mol Biol Evol 9 552 569 Rousset F 1996 Equilibrium values of measures of population subdivision for stepwise mutation processes Genetics 142 1357 1362 Slatkin M 1991 Inbreeding coefficients and coalescence times Genet Res Camb 58 167 175 Slatkin M 1994a Linkage disequilibrium in growing and stable populations Genetics 137 331 336 Slatkin M 1994b An exact test for neutrality based on the Ewens sampling distribution Genet Res 64 1 71 74 Manual Arlequin ver 1 1 References 61 Slatkin M 1995 A measure of population subdivision based on microsatellite allele frequencies Genetics 139 457 462 Slatkin M 1996 A correction to the exact test based on the Ewens sampling distribution Genet R
18. urveys in Evolutionary Biology edited by Futuyama and J D Antonovics Oxford University Press New York Jukes T and Cantor C 1969 Evolution of protein molecules In Mammalian Protein Metabolism edited by Munro HN New York Academic press p 21 132 Kimura M 1980 A simple method for estimating evolutionary rate of base substitution through comparative studies of nucleotide sequences J Mol Evol 16 111 120 Kumar S Tamura K and M Nei 1993 MEGA Molecular Evolutionary Genetic Analysis ver 1 0 The Pennsylvania State University University Park PA 16802 Lange K 1997 Mathematical and Statistical Methods for Genetic Analysis Springer New York Levene H 1949 On a matching problem arising in genetics Annals of Mathematical Statistics 20 91 94 Lewontin R C 1964 The interaction of selection and linkage I General considerations heterotic models Genetics 49 49 67 Lewontin R C and K Kojima 1960 The evolutionary dynamics of complex polymorphisms Evolution 14 450 472 Long J C 1986 The allelic correlation structure of Gainj and Kalam speaking people I The estimation and interpretation of Wright s F statistics Genetics 112 629 647 Michalakis Y and Excoffier L 1996 A generic estimation of population subdivision using distances between alleles with special reference to microsatellite loci Genetics 142 1061 1064 Nei M 1987 Molecular Evolutionary Genetics Columbia Unive
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