The role of complementary bipartite visual analytical representations in the analysis of SNPs: A case study in ancestral informative markers

Journal of the American Medical Informatics Association

Volumn 19, Issue E1, 2012, Pages

  Bhavnani, Suresh K ^a   Bellala, Gowtham ^b,f   Victor, Sundar ^a   Bassler, Kevin E ^c,d   Visweswaran, Shyam ^e  

^a UNIVERSITY OF TEXAS MEDICAL BRANCH   (United States)

^b UNIVERSITY OF MICHIGAN   (United States)

^c University of Houston   (United States)

^d UNIVERSITY OF HOUSTON   (United States)

^e UNIVERSITY OF PITTSBURGH SCHOOL OF MEDICINE   (United States)

^f HEWLETT PACKARD LABORATORIES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANALYTIC METHOD; ARTICLE; BIPARTITE NETWORK; CASE STUDY; CIRCOS IDEOGRAM; CONTROLLED STUDY; DATA ANALYSIS; GENOMICS; GENOTYPE; HEAT MAP; HUMAN; INTERMETHOD COMPARISON; PHYLOGENETIC TREE; QUANTITATIVE ANALYSIS; SINGLE NUCLEOTIDE POLYMORPHISM;

ALGORITHMS; ANALYSIS OF VARIANCE; COMPUTATIONAL BIOLOGY; HUMANS; MATHEMATICAL CONCEPTS; MULTIVARIATE ANALYSIS; POLYMORPHISM, SINGLE NUCLEOTIDE;

EID: 84863543326     PISSN: 10675027     EISSN: 1527974X     Source Type: Journal    
DOI: 10.1136/amiajnl-2011-000745     Document Type: Article

References (36)

1. Kreuzer K, Massey A. Molecular Biology and Biotechnology: A Guide for Teachers. 3rd edn. Washington, D.C: ASM Press, 2007.
2. Lewis CM. Genetic association studies: Design, analysis and interpretation. Brief Bioinform 2002;3:146-53.
3. Tang H, Quertermous T, Rodriguez B, et al. Genetic structure, self-identified race/ethnicity, and confounding in case-control association studies. Am J Hum Genet 2005;76:268-75.
4. Parra FC, Amado RC, Lambertucci JR, et al. Color and genomic ancestry in Brazilians. Proc Natl Acad Sci U S A 2003;100:177-82.
5. Paschou P, Lewis J, Javed A, et al. Ancestry informative markers for fine-scale individual assignment to worldwide populations. J Med Genet 2010;47:835-47.
6. Patterson N, Price AL, Reich D. Population structure and eigenanalysis. PLoS Genet 2006;2:e190.
7. Witherspoon DJ, Wooding S, Rogers AR, et al. Genetic similarities within and between human populations. Genetics 2007;176:351-9.
8. Nassir R, Kosoy R, Tian C, et al. An ancestry informative marker set for determining continental origin: validation and extension using human genome diversity panels. BMC Genet 2009;10:39.
9. Pritchard JK, Stephens M, Donnelly P. Inference of population structure using multilocus genotype data. Genetics 2000;155:945-59.
10. Hoggart CJ, Shriver MD, Kittles RA, et al. Design and analysis of admixture mapping studies. Am J Hum Genet 2004;74:965-78.
11. Aldrich MC, Selvin S, Hansen HM, et al. Comparison of statistical methods for estimating genetic admixture in a lung cancer study of African Americans and Latinos. Am J Epidemiol 2008;168:1035-46.
12. Tsai HJ, Choudhry S, Naqvi M, et al. Comparison of three methods to estimate genetic ancestry and control for stratification in genetic association studies among admixed populations. Hum Genet 2005;118:424-33.
13. International HapMap Consortium. The international HapMap project. Nature 2003;426:789-96.
14. Kosoy R, Nassir R, Tian C, et al. Ancestry informative marker sets for determining continental origin and admixture proportions in common populations in America. Hum Mutat 2009;30:69-78.
15. Kidd JR, Friedlaender FR, Speed WC, et al. Analyses of a set of 128 ancestry informative single-nucleotide polymorphisms in a global set of 119 population samples. Investig Genet 2011;2:1.
16. Bhavnani SK, Abraham A, Demeniuk C, et al. Network analysis of toxic chemicals and symptoms: implications for designing first-responder systems. AMIA Annu Symp Proc 2007:51-5.
17. Bhavnani SK, Bellala G, Ganesan A, et al. The nested structure of cancer symptoms: implications for analyzing co-occurrence and managing symptoms. Methods Inf Med 2010;49:581-91.
18. Bhavnani SK, Carini S, Ross J, et al. Network analysis of clinical trials on depression: implications for comparative effectiveness research. AMIA Annu Symp Proc 2010:51-5.
19. Albert RK. Boolean modeling of genetic regulatory networks. In: Complex Networks editors: Ben-Naim E, Frauenfelder H, Toroczkai Z, eds. Berlin: Springer-Verlag, 2004:459-79.
20. Goh KI, Cusick ME, Valle D, et al. The human disease network. Proc Natl Acad Sci U S A 2007;104:8685-90.
21. Ideker T, Sharan R. Protein networks in disease. Genome Res 2008;18:644-52.
22. Newman M. Networks: An Introduction. New York, NY: Oxford University Press, 2010.
23. Batagelj V, Mrvar A. Pajek - analysis and visualization of large networks. In: Jünger M, Mutzel P, eds. Graph Drawing Software, Berlin: Springer, 2003:77-103.
24. Kamada T, Kawai S. An algorithm for drawing general undirected graphs. Inf Process Lett 1989;31:7-15.
25. Nooy W, Mrvar A, Batagelj V. Exploratory Social Network Analysis with Pajek. New York, NY: Cambridge University Press, 2005.
26. Johnson RA, Wichern DW. Applied Mutlivariate Statistical Analysis. Upper Saddle River, NJ: Prentice-Hall, 1998.
27. Krzywinski M, Schein J, Birol I, et al. Circos: an information aesthetic for comparative genomics. Genome Res 2009;19:1639-45.
28. Borgatti SP, Halgin D. Analyzing affiliation networks. In: Carrington P, Scott J, eds. The Sage Handbook of Social Network Analysis. Thousand Oaks, CA: Sage Publications, 2011.
29. Newman ME, Girvan M. Finding and evaluating community structure in networks. Phys Rev E Stat Nonlin Soft Matter Phys 2004;69:026113.
30. Guimera R, Sales-Pardo M, Amaral LA. Module identification in bipartite and directed networks. Phys Rev E Stat Nonlin Soft Matter Phys 2007;76:036102.
31. Becker KG, Barnes KC, Bright TJ, et al. The genetic association database. Nat Genet 2004;36:431-2.
32. Barber MJ. Modularity and community detection in bipartite networks. Phys Rev E Stat Nonlin Soft Matter Phys 2007;76:066102.
33. Johnson B, Shneiderman B. Tree-Maps: a space-filling approach to the visualization of hierarchical information structures. Proc. of the 2nd International IEEE Visualization Conference (San Diego, Oct. 1991) 284-91.
34. Filippova D, Shneiderman B. Interactive exploration of multivariate categorical data: exploiting ranking criteria to reveal patterns and outliers, Human-Computer Interaction Lab, University of Maryland, Technical Report # HCIL-2009-38. 2009.
35. Schulz HJ, John M, Unger A, et al. Visual Analysis of Bipartite Biological Networks. Proc of Eurographics Workshop on Visual Computing for Biomedicine, Delft, Netherlands. October 2008., pp. 135-42.
36. Stolte C, Tang D, Hanrahan P. Polaris: a system for query, analysis, and visualization of multidimensional databases. IEEE Trans Visual Comput Graph 2002;8:75-84.