Population Genetics statistical program
Arlequin 3.11 (download) & manual download

Homepage =>> http://cmpg.unibe.ch/software/arlequin3


<가능한 분석>
  The analyses Arlequin can perform on the data fall into two main categories: intra-population and inter-population methods. In the first category statistical information is extracted independently from each population, whereas in the second category, samples are compared to each other.

Intra-population methods:

Short description:

Standard indices

Some diversity measures like the number of polymorphic sites, gene diversity.

Molecular diversity

Calculates several diversity indices like nucleotide diversity, different estimators of the population parameter q.

Mismatch distribution

The distribution of the number of pairwise differences between haplotypes, from which parameters of a demographic (NEW in ver 3.x) or spatial population expansion can be estimated

Haplotype frequency estimation

Estimates the frequency of haplotypes present in the population by maximum likelihood methods.

Gametic phase estimation
(NEW in ver 3.x)

Estimates the most like gametic phase of multi-locus genotypes using a pseudo-Bayesian approach (ELB algorithm).

Linkage disequilibrium

Test of non-random association of alleles at different loci.

Hardy-Weinberg equilibrium

Test of non-random association of alleles within diploid individuals.

Tajima’s neutrality test

Test of the selective neutrality of a random sample of DNA sequences or RFLP haplotypes under the infinite site model.

Fu's FS neutrality test

Test of the selective neutrality of a random sample of DNA sequences or RFLP haplotypes under the infinite site model.

Ewens-Watterson neutrality test

Tests of selective neutrality based on Ewens sampling theory under the infinite alleles model.

Chakraborty’s amalgamation test

A test of selective neutrality and population homogeneity. This test can be used when sample heterogeneity is suspected.

Minimum Spanning Network (MSN)

Computes a Minimum Spanning Tree (MST) and Network (MSN) among haplotypes. This tree can also be computed for all the haplotypes found in different populations if activated under the AMOVA section.

   

Inter-population methods:

Short description:

Search for shared haplotypes between populations

Comparison of population samples for their haplotypic content. All the results are then summarized in a table.

AMOVA

Different hierarchical Analyses of Molecular Variance to evaluate the amount of population genetic structure.

Pairwise genetic distances

FST based genetic distances for short divergence time.

Exact test of population differentiation

Test of non-random distribution of haplotypes into population samples under the hypothesis of panmixia.

Assignment test of genotypes

Assignment of individual genotypes to particular populations according to estimated allele frequencies.

   

Mantel test:

Short description:

Correlations or partial correlations between a set of 2 or 3 matrices

Can be used to test for the presence of isolation-by-distance

   

<ScreenShots>
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Posted by 토리군
이 프로그램은 사용이 쉬운 편이다.

여기서는 STR 분석을 예로 설명해 보았다.

먼저 분석된 데이터를 엑셀에서 아래와 같은 양식으로 데이타를 정리한다.
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* 두 allele을 따로따로 입력했을 경우,
CONCATENATE 함수를 이용하면 쉽게 두 문자를 합쳐서 위 양식을 만들 수 있다.
(각 marker의 두 allele은 / 으로 구분한다.)

위 양식을 복사해서 txt 파일을 만든다.
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제일 윗줄에는 marker 이름, 아래에는 각 marker의 allele을 적는다. marker 사이는 tab으로 띄워준다.
(엑셀에서 복사하면 tab으로 띄워져 있으니 그냥 두면 된다.)

Powermarker를 실행한다.
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Project가 없을경우, Project를 생성한다. 명칭은 원하는대로...

그리고 Dataset을 클릭한다.
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Browse를 클릭해서 이전에 만든 텍스트 파일을 불러온다. 그리고 Next

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제일 윗줄을 기준으로, 각 라인이 marker인지, category인지 등을 지정한다. Next..
최종적으로 입력된 데이터가 나온다. Finish.

이렇게 데이터가 입력된다.
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이제 분석...
메뉴의 Analysis 에서 원하는 분석방법을 선택한다.
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먼저 Summary Statistics를 들어가보면,
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이렇게 나온다. Option에서 원하는 분석을 선택한다.
그리고 왼쪽의 Data and Result의 목록에서 아까 입력한 데이터를 선택.
Submit을 클릭하면 분석이 시작되고 결과가 나타난다.

아래는 Hardy Weinberg test 분석의 경우...
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마찬가지로, 원하는 분석을 선택하고 데이터를 선택하고 Submit. 하면...

아래처럼 결과가 출력된다.
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이 결과는 본문의 셀을 클릭하거나,
Explorer 창에서 오른쪽 클릭후 Excel로 열기를 선택하면 Excel로 변환할 수 있다.

Posted by 토리군
집단유전학 통계 프로그램(Population genetics data analysis program)
Powermarker  v3.25 (download)  &  manual download
(.Net framework 1.1 must installed)

Homepage =>> http://statgen.ncsu.edu/powermarker/index.html


<가능한 분석 목록>
Summary statistics
  • Compute sample size
  • Compute number of observation
  • Compute allele number
  • Compute availability (1 - missing proportion)
  • Compute gene diversity using biased or unbiased version
  • Compute polymorphism information content
  • Compute heterozygosity
  • Compute stepwise mutation index which was defined as the maximal proportion of alleles which follow stepwise mutation pattern
  • Compute moment estimator or maximum likelihood estimator of within-population inbreeding coefficient
  • Summarize result at any level
  • Bootstrap across loci to estimate confidence intervals
  • Estimate allele frequency and its variance
  • Bootstrap across individual to estimate confidence interval
  • Estimate genotype frequency and allele covariance
  • Bootstrap across individual to estimate confidence interval
  • Estimate haplotype frequency using EM algorithm
  • Estimate haplotype frequency using BisectionEM algorithm
  • Estimate haplotype frequency using TrioEM algorithm
  • Assign haplotype probabilities for each individual
  • Test Hardy-Weinberg equilibrium by ChiSquare test
  • Test Hardy-Weinberg equilibrium by likelihood ratio test
  • Test Hardy-Weinberg equilibrium by Exact test
  • Compute Hardy-Weinberg disequilibrium statistics
  • Bootstrap across individual to estimate confidence interval for Hardy-Weinberg disequilibrium statistics
  • Estimate linkage disequilibrium D
  • Estimate D'
  • Estimate RSquare
  • Estimate population attributable risk
  • Estimate proportional difference
  • Estimate Yule's Q
  • Estimate two-loci haplotype frequency for computing LD statistics
  • Test two-loci linkage equilibrium by ChiSquare test
  • Test two-loci linkage equilibrium by Exact test
  • Test multi-loci linkage equilibrium by Exact test
  • Prepare 2D matrix for 2D plot
Population structure
  • Estimate population structure with admixture
  • Estimate population structure without admixture
  • Estimate classic coancestry matrix
  • Estimate population specific coancestry matrix
  • Estimate classic two-level F-statistics assuming Hardy-Weinberg equilibrium
  • Estimate classic two-level F-statistics considering inbreeding
  • Estimate classic three-level F-statistics assuming Hardy-Weinberg equilibrium
  • Estimate classic three-level F-statistics considering inbreeding
  • Estimate population specific two-level F-statistics assuming Hardy-Weinberg equilibrium
  • Estimate population specific two-level F-statistics considering inbreeding
  • Bootstrap across loci to estimate confidence interval
Phylogenetic analysis
  • Estimate frequency from DataSet
  • Estimate distance based Frequency data using 19 different methods
  • Construct UPGMA tree
  • Construct NJ tree
  • Bootstrap across loci to construct multiple trees for tree consensus
Association study
  • Allele test
  • Genotype test
  • Trend test
  • Distance test
  • Exact test
  • Genotype based F-test
  • Haplotype trend regression for binary and quantitative traits
Design
  • Choose core set of lines by allele number, allelic diversity, allelic entropy. Selection can be done with simulated annealing, random search or exhaustive search under general constrains
  • Choose haplotype tagging markers from haplotype data
  • Choose haplotype tagging markers from genotype data
  • Choose haplotype tagging markers from trio data
Tools
  • Mantel test
  • Contigency table analysis
  • SNP identification from sequences
  • Parse Structure's result
  • SNP simulation under coalescence model
  • SNP simulation under coalescence model with recombination hotspots


<ScreenShots>

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Posted by 토리군