NetView: A High-Definition Network-Visualization Approach to Detect Fine-Scale Population Structures from Genome-Wide Patterns of Variation

PLoS ONE

Volumn 7, Issue 10, 2012, Pages

  Neuditschko, Markus ^a   Khatkar, Mehar S ^a   Raadsma, Herman W ^a  

^a UNIVERSITY OF SYDNEY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

ANALYTIC METHOD; ARTICLE; GENETIC ANALYSIS; GENETIC DISTANCE; GENOTYPE; HAPLOTYPE; HIGH THROUGHPUT SEQUENCING; LEARNING ALGORITHM; NETVIEW; PHENOTYPE; PHYLOGENY; POPULATION STRUCTURE; PRINCIPAL COMPONENT ANALYSIS; PROCESS OPTIMIZATION; SINGLE NUCLEOTIDE POLYMORPHISM; SUPER PARAMAGNETIC CLUSTERING; VALIDATION PROCESS;

CLUSTER ANALYSIS; GENETIC VARIATION; GENOME-WIDE ASSOCIATION STUDY; HUMANS;

BOS;

EID: 84868271208     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0048375     Document Type: Article

References (73)

1. Serre D, Montpetit A, Paré G, Engert JC, Yusuf S, et al. (2008) Correction of population stratification in large multi-ethnic association studies. PLoS One 3: e1382.
2. Bowden R, MacFie TS, Myers S, Hellenthal G, Nerrienet E, et al. (2012) Genomic tools for evolution and conservation in the chimpanzee: Pan troglodytes ellioti is a genetically distinct population. PLoS Genet 8: e1002504.
3. Pushkarev D, Neff NF, Quake SR, (2009) Single-molecule sequencing of an individual human genome. Nat Biotechnol 27: 847-850.
4. Schuster SC, (2008) Next-generation sequencing transforms today's biology. Nat Methods 5: 16-18.
5. Bentley DR, Balasubramanian S, Swerdlow HP, Smith GP, Milton J, et al. (2008) Accurate whole human genome sequencing using reversible terminator chemistry. Nature 456: 53-59.
6. Gompert Z, Forister ML, Fordyce JA, Nice CC, Williamson RJ, et al. (2010) Bayesian analysis of molecular variance in pyrosequences quantifies population genetic structure across the genome of Lycaeides butterflies. Mol Ecol 19: 2455-2473.
7. Shriver MD, Mei R, Parra E, Sonpar V, Halder I, et al. (2005) Large-scale SNP analysis reveals clustered and continuous patterns of human genetic variation. Hum Genomics 2: 81-89.
8. Stoneking M, Krause J, (2011) Learning about human population history from ancient and modern genomes. Nat Rev Genet 12: 603-614.
9. Rasmussen M, Guo X, Wang Y, Lohmueller KE, Rasmussen S, et al. (2011) An Aboriginal Australian genome reveals separate human dispersals into Asia. Science 334: 94-98.
10. Decker JE, Pires JC, Conant GC, McKay SD, Heaton MP, et al. (2009) Resolving the evolution of extant and extinct ruminants with high-throughput phylogenomics. Proc Natl Acad Sci U S A 106: 18644-18649.
11. Gautier M, Laloë D, Moazami-Goudarzi K, (2010) Insights into the genetic history of French cattle from dense SNP data on 47 worldwide breeds. PLoS One 5: e13038.
12. Kijas JW, Townley D, Dalrymple BP, Heaton MP, Maddox JF, et al. (2009) A genome wide survey of SNP variation reveals the genetic structure of sheep breeds. PLoS One 4: e4668.
13. Vonholdt BM, Pollinger JP, Lohmueller KE, Han E, Parker HG, et al. (2010) Genome-wide SNP and haplotype analyses reveal a rich history underlying dog domestication. Nature 464: 898-902.
14. Cortes AJ, Chavarro MC, Blair MW, (2011) SNP marker diversity in common bean (Phaseolus vulgaris L.). Theor Appl Genet 123: 827-845.
15. Menozzi P, Piazza A, Cavalli-Sforza L, (1978) Synthetic maps of human gene frequencies in Europeans. Science 201: 786-792.
16. Pritchard JK, Stephens M, Donnelly P, (2000) Inference of population structure using multilocus genotype data. Genetics 155: 945-959.
17. Falush D, Stephens M, Pritchard JK, (2003) Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics 164: 1567-1587.
18. Alexander DH, Novembre J, Lange K, (2009) Fast model-based estimation of ancestry in unrelated individuals. Genome Res 19: 1655-1664.
19. Lawson DJ, Hellenthal G, Myers S, Falush D, (2012) Inference of population structure using dense haplotype data. PLoS Genet 8: e1002453.
20. Patterson N, Price AL, Reich D, (2006) Population structure and eigenanalysis. PLoS Genet 2: e190.
21. Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, et al. (2006) Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet 38: 904-909.
22. Gao X, Starmer J, (2008) AWclust: point-and-click software for non-parametric population structure analysis. BMC Bioinformatics 9: 77.
23. Reeves PA, Richards CM, (2009) Accurate inference of subtle population structure (and other genetic discontinuities) using principal coordinates. PLoS One 4: e4269.
24. Hartigan JA, Wong MA, (1979) Algorithm AS 136: a k-means clustering algorithm. J R Stat Soc Ser C Appl Stat 28: 100-108.
25. Fraley C, Raftery A, (2012) Model-based methods of classification: using the mclust software in chemometrics. J Stat Softw 18: 1-13.
26. Liu N, Zhao H, (2006) A non-parametric approach to population structure inference using multilocus genotypes. Hum Genomics 2: 353-364.
27. Caliński T, Harabasz J, (1974) A dendrite method for cluster analysis. Commun Stat 3: 1-27.
28. Schwarz G, (1978) Estimating the dimension of a model. Ann Stat 6: 461-464.
29. Lawson DJ, Falush D (2012) Population identification using genetic data. Annu Rev Genomics Hum Genet: "In press".
30. Intarapanich A, Shaw P, Assawamakin A, Wangkumhang P, Ngamphiw C, et al. (2009) Iterative pruning PCA improves resolution of highly structured populations. BMC Bioinformatics 10: 382.
31. Gibbs RA, Taylor JF, Van Tassell CP, Barendse W, Eversole KA, et al. (2009) Genome-wide survey of SNP variation uncovers the genetic structure of cattle breeds. Science 324: 528-532.
32. Parsons L, Haque E, Liu H, (2004) Subspace clustering for high dimensional data: a review. SIGKDD Explor Newsl 6: 90-105.
33. Tian C, Plenge RM, Ransom M, Lee A, Villoslada P, et al. (2008) Analysis and application of European genetic substructure using 300 K SNP information. PLoS Genet 4: e4.
34. Kim JJ, Verdu P, Pakstis AJ, Speed WC, Kidd JR, et al. (2005) Use of autosomal loci for clustering individuals and populations of East Asian origin. Human Genet 117: 511-519.
35. Lao O, van Duijn K, Kersbergen P, de Knijff P, Kayser M, (2006) Proportioning whole-genome single-nucleotide-polymorphism diversity for the identification of geographic population structure and genetic ancestry. Am J Hum Genet 78: 680-690.
36. Patterson N, Hattangadi N, Lane B, Lohmueller KE, Hafler DA, et al. (2004) Methods for high-density admixture mapping of disease genes. Am J Hum Genet 74: 979-1000.
37. Tang H, Peng J, Wang P, Risch NJ, (2005) Estimation of individual admixture: analytical and study design considerations. Genetic Epidemiol 28: 289-301.
38. Behar DM, Yunusbayev B, Metspalu M, Metspalu E, Rosset S, et al. (2010) The genome-wide structure of the Jewish people. Nature 466: 238-242.
39. Bryc K, Auton A, Nelson MR, Oksenberg JR, Hauser SL, et al. (2010) Genome-wide patterns of population structure and admixture in West Africans and African Americans. Proc Natl Acad Sci U S A 107: 786-791.
40. Simón-Sánchez J, Kilarski LL, Nalls MA, Martinez M, Schulte C, et al. (2012) Cooperative genome-wide analysis shows increased homozygosity in early onset Parkinson's disease. PLoS One 7: e28787.
41. Neuditschko M, Maxa J, Russ I, Schaer J, Medugrac I (2010) Spinnet: a new tool to study the population structure with a genome-wide SNP survey. Proceedings of the 9th World Congress on Genetics Applied to Livestock production. Leipzig, Germany.
42. Rozenfeld AF, Arnaud-Haond S, Hernández-García E, Eguíluz VM, Serrão EA, et al. (2008) Network analysis identifies weak and strong links in a metapopulation system. Proc Natl Acad Sci U S A 105: 18824-18829.
43. May RM, Lloyd AL, (2001) Infection dynamics on scale-free networks. Phys Rev E Stat Nonlin Soft Matter Phys 64: 066112.
44. Broder A, Kumar R, Maghoul F, Raghavan P, Rajagopalan S, et al. (2000) Graph structure in the web. Comput Netw 33: 309-320.
45. Girvan M, Newman ME, (2002) Community structure in social and biological networks. Proc Natl Acad Sci U S A 99: 7821-7826.
46. Leicht EA, Holme P, Newman ME, (2006) Vertex similarity in networks. Phys Rev E Stat Nonlin Soft Matter Phys 73: 026120.
47. Bagrow JP, Bollt EM, (2005) Local method for detecting communities. Phys Rev E Stat Nonlin Soft Matter Phys 72: 046108.
48. Wu F, Huberman BA, (2004) Finding communities in linear time: a physics approach. Eur Phys J B 38: 331-338.
49. Reichardt J, Bornholdt S, (2004) Detecting fuzzy community structures in complex networks with a Potts model. Phys Rev Lett 93: 218701.
50. Blatt M, Wiseman S, Domany E, (1996) Superparamagnetic clustering of data. Phys Rev Lett 76: 3251-3254.
51. Tsafrir D, Tsafrir I, Ein-Dor L, Zuk O, Notterman DA, et al. (2000) Sorting points into neighborhoods (SPIN): data analysis and visualization by ordering distance matrices. Bioinformatics 21: 2301-2308.
52. Tetko IV, Facius A, Ruepp A, Mewes HW, (2005) Super paramagnetic clustering of protein sequences. BMC Bioinformatics 6: 82.
53. Pemberton TJ, Wang C, Li JZ, Rosenberg NA, (2010) Inference of unexpected genetic relatedness among individuals in HapMap Phase III. Am J Hum Genet 87: 457-464.
54. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, et al. (2007) PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 81: 559-575.
55. Wright S, (1950) Genetical structure of populations. Nature 166: 247-249.
56. Nei M, (1972) Genetic distance between populations. Am Nat 106: 283-292.
57. Gao X, Martin ER, (2009) Using allele sharing distance for detecting human population stratification. Hum Hered 68: 182-191.
58. Barad O (2003) Advanced clustering algorithm for gene expression analysis using statistical methods [Msc. thesis]. Israel: Weizmann Institute.
59. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, et al. (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13: 2498-2504.
60. Brohée S, Faust K, Lima-Mendez G, Vanderstocken G, van Helden J, (2008) Network Analysis Tools: from biological networks to clusters and pathways. Nat Protoc 3: 1616-1629.
61. Tenesa A, Navarro P, Hayes BJ, Duffy DL, Clarke GM, et al. (2007) Recent human effective population size estimated from linkage disequilibrium. Genome Res 17: 520-526.
62. Frazer KA, Ballinger DG, Cox DR, Hinds DA, Stuve LL, et al. (2007) A second generation human haplotype map of over 3.1 million SNPs. Nature 449: 851-861.
63. Glorfeld LW, (1995) An improvement on Horn's parallel analysis methodology for selecting the correct number of factors to retain. Educ Psychol Meas 55: 377-393.
64. Altshuler DM, Gibbs RA, Peltonen L, Dermitzakis E, Schaffner SF, et al. (2010) Integrating common and rare genetic variation in diverse human populations. Nature 467: 52-58.
65. Li JZ, Absher DM, Tang H, Southwick AM, Casto AM, et al. (2008) Worldwide human relationships inferred from genome-wide patterns of variation. Science 319: 1100-1104.
66. Engelhardt BE, Stephens M, (2010) Analysis of population structure: a unifying framework and novel methods based on sparse factor analysis. PLoS Genet 6: e1001117.
67. Gusev A, Palamara PF, Aponte G, Zhuang Z, Darvasi A, et al. (2011) The architecture of long-range haplotypes shared within and across populations. Mol Biol Evol 29: 473-486.
68. Saitou N, Nei M, (1987) The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol 4: 406-425.
69. Johnson JA, Talbot SL, Sage GK, Burnham KK, Brown JW, et al. (2010) The use of genetics for the management of a recovering population: temporal assessment of migratory peregrine falcons in North America. PLoS One 5: e14042.
70. DeSalle R, Amato G, (2004) The expansion of conservation genetics. Nat Rev Genet 5: 702-712.
71. Genome 10K Community of Scientists (2009) Genome 10K: a proposal to obtain whole-genome sequence for 10,000 vertebrate species. J Hered 100: 659-674.
72. Pool JE, Hellmann I, Jensen JD, Nielsen R, (2010) Population genetic inference from genomic sequence variation. Genome Res 20: 291-300.
73. Kijas JW, Lenstra JA, Hayes B, Boitard S, Porto Neto LR, et al. (2012) Genome-wide analysis of the world's sheep breeds reveals high levels of historic mixture and strong recent selection. PLoS Biol 10: e1001258.