1 / 46

人类群体遗传学 基本原理和分析方法

中国科学院上海生命科学研究院研究生课程 人类群体遗传学. 人类群体遗传学 基本原理和分析方法. 中科院 - 马普学会计算生物学伙伴研究所. 徐书华 金 力. 第八讲. 人群遗传结构分析 ( II ). 第八讲. 人群分化与遗传多样性 STRUCTURE 分析 文件格式 参数设定 结果解释 软件展示 STRUCTURE 2.2.3. 人群遗传结构分析. 人群遗传结构分析 Gene tree based AMOVA (hierarchical F statistics) Factor analysis

jeb
Télécharger la présentation

人类群体遗传学 基本原理和分析方法

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. 中国科学院上海生命科学研究院研究生课程人类群体遗传学中国科学院上海生命科学研究院研究生课程人类群体遗传学 人类群体遗传学基本原理和分析方法 中科院-马普学会计算生物学伙伴研究所 徐书华 金 力

  2. 第八讲 人群遗传结构分析(II)

  3. 第八讲 • 人群分化与遗传多样性 • STRUCTURE分析 • 文件格式 • 参数设定 • 结果解释 • 软件展示 • STRUCTURE 2.2.3

  4. 人群遗传结构分析 • 人群遗传结构分析 • Gene tree based • AMOVA (hierarchical F statistics) • Factor analysis • Principle Component analysis • STRUCTURE analysis

  5.   

  6.   

  7. Geographical distribution HGDP samples (52 populations)

  8. Previous genome-wide data in HGDP panel • Science 2002 • 52 populations, 1,056 individuals • 377 autosomal STRs • Plos Genet 2005 • 52 populations, 1,048 individuals • 783 STRs, 210 indels • Nature Genetics 2006 • 52 populations, 927 individuals • 3,024 SNPs in 36 genomic regions

  9. NIH & University of Michigan Stanford University

  10. Genotype, haplotype and copy-number variation in worldwide human populations • Study design: • Genome-wide patterns of variation; • Fine-scale population structure. • Data structure: • 29 HGDP populations, 485 individuals. • 4 HapMap populations, 112 individuals. • 525,910 SNPs, 396 CNVs (Illumina HumanHap550K). • New findings: • Increasing linkage disequilibrium is observed with increasing geographic distance from Africa (a serial founder effect). • The global distribution of CNVs largely accords with population structure analyses for SNP data sets of similar size. • Conclusions: • Support the utility of CNVs in human population-genetic research.

  11. Worldwide Human Relationships Inferred from Genome-Wide Patterns of Variation • Study design: • Human genetic diversity; • Fine-scale population structure. • Data structure: • 51 populations; 938 individuals. • 650,000 SNPs (Illumina HumanHap650K). • New findings: • The relationship between haplotype heterozygosity and geography was consistent with the hypothesis of a serial founder effect with a single origin in sub-Saharan Africa. • Observed a pattern of ancestral allele frequency distributions that reflects variation in population dynamics among geographic regions. • Conclusions: • This data set allows the most comprehensive characterization to date of human genetic variation. Individual ancestry and population substructure are detectable with very high resolution.

  12. NJ tree based on SNP genotypes

  13. Population structure inferred by STRUCTURE

  14. Maximum likelihood tree of 51 populations Oceania America 150,000 SNPs East Asia South/Central Asia Europe Middle East North Africa

  15. MDS plots

  16. MDS plots of individuals SNP Haplotype CNV

  17. MDS Chrom 21 220 SNPs Nei’s DA

  18. PCA plots

  19. PCA of populations

  20. PCA of individuals

  21. STR can not, SNP can Europe Middle East

  22. Han and Northern Han

  23. 56 ethnic groups in China

  24. Genetic structure of language families

  25. Two types of genetic structure

  26. All other Han Chinese Shy blue: CN-GA CN-PH Olive green: TW-HA TW-HB Brown: SG-CH

  27. Inference on population structure using multi-locus genotype dataSTRUCTURE V2.2.3 Pritchard, Stephens, and Donnelly (2000) Falush, Stephens, and Pritchard (2003)

  28. Main objective • Assign individuals to populations on the bases of their genotypes, while simultaneously estimating population allele frequencies

  29. Other objectives • Begin with a set of predefined populations and to classify individuals of unknown origin • Identify the extent of admixture of individuals • Infer the origin of particular loci in the sampled individuals

  30. Structure is a Model Based method of clustering (we must be assumptions about a lot of parameters and distributions)

  31. Four basic models • Model without admixture each individual is assumed to originate in one (only one) of K populations • Model with admixture each individual is assumed to have inherited some proportion of its ancestry from each of K populations

  32. Four basic models • Linkage model “Chunks” of chromosomes as derived as intact units from one or another K population and all allele copies on the same “chunk” derive from the same population. The model consider the derived correlations in ancestry

  33. Four basic models • F model The populations all diverged from a common ancestral population at the same time, but allows that the populations may have experienced different amounts of drift since the divergence event

  34. Assumptions • “Our main modeling assumptions are Hardy-Weinberg equilibrium within populations and complete linkage equilibrium between loci within populations” • “Loosely speaking, the idea here is that the model accounts for the presence oh HWD or LD by introducing population structure and attempts to find populations groupings that (as far as possible) are not in disequilibrium”

  35. Data • Consider a sample of N individuals each one genotyped at L loci • Assume that the individuals represent a mixture of K unobserved populations (K unknown) • If diploid, we have an N×2L data matrix X • If n-ploid X is N× where Jl is the number of alleles at the lth locus

  36. Input file format

  37. Parameter setting • Main parameters (mainparams.txt) • Extra parameters (extraparams.txt)

  38. 软件演示 (structure)

  39. Summary plot of estimates of individual membership fraction

  40. 常用软件 • STRUCTURE • http://pritch.bsd.uchicago.edu/software/structure2_2.html • EIGENSOFT • http://genepath.med.harvard.edu/~reich/Software.htm • SPSS

  41. 练习 • 利用HapMap数据进行STRUCTURE分析; • http://www.hapmap.org

More Related