Bioinformatics Advance Access originally published online on August 5, 2004
Bioinformatics 2005 21(2):263-265; doi:10.1093/bioinformatics/bth457
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Bioinformatics vol. 21 issue 2 © Oxford University Press 2005; all rights reserved.
Haploview: analysis and visualization of LD and haplotype maps
1 Whitehead Institute for Biomedical Research Cambridge, MA 02142, USA
2 MIT Media Lab Cambridge, MA 02139, USA
3 Broad Institute of Harvard and MIT Cambridge, MA, USA
*To whom correspondence should be addressed.
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Abstract |
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 TOP Abstract INTRODUCTIONFEATURESIMPLEMENTATIONREFERENCES |
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Summary: Research over the last few years has revealed significant haplotype structure in the human genome. The characterization of these patterns, particularly in the context of medical genetic association studies, is becoming a routine research activity. Haploview is a software package that provides computation of linkage disequilibrium statistics and population haplotype patterns from primary genotype data in a visually appealing and interactive interface.
Availability: http://www.broad.mit.edu/mpg/haploview/
Contact: jcbarret{at}broad.mit.edu
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INTRODUCTION |
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TOPAbstractINTRODUCTIONFEATURESIMPLEMENTATIONREFERENCES |
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Knowledge of local linkage disequilibrium (LD) and common haplotype patterns in disease association and positional cloning studies is becoming increasingly widespread since it has become clear (Van Eerdewegh et al., 2002; Rioux et al., 2001; Geesaman et al., 2003; Stoll et al., 2004) that intelligent use of this information has the potential to make them much more comprehensive and efficient. Early studies identifying unexpected extent of correlation and structure in haplotype patterns (Reich et al., 2001; Daly et al., 2001; Gabriel et al., 2002) have led to the initiation of the Human Haplotype Map project (HapMap) to make this information available to all medical genetics researchers (International HapMap Consortium, 2003). Given the dramatic increase in the size and number of disease association studies worldwide and the enormous amount of public genotype data from HapMap, tools for analyzing, interpreting and visualizing these data are of critical importance to researchers everywhere.
Haploview is designed to provide a comprehensive suite of tools for haplotype analysis for a wide variety of dataset sizes. Haploview generates marker quality statistics, LD information, haplotype blocks, population haplotype frequencies and single marker association statistics in a user-friendly format. All the features are customizable and all computations performed in real time, even for datasets with hundreds of individuals and hundreds of markers.
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FEATURES |
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Haploview accepts input in a variety of formats. Pedigree data can be loaded as either partially or fully phased chromosomes or as unphased diplotypes in the standard Linkage format. The latter format also allows the user to specify family structure information as well as disease affection or case/control status. Marker information, including name and location is loaded separately. Haploview also directly accepts genotype data dumped from the Human HapMap website (http://www.hapmap.org). A graphical genome browser maintained at that site allows researchers to navigate to a particular region of the genome and dump HapMap genotype data for all genotyped markers in the selected region in a format accepted by Haploview.
Upon loading a dataset, the software presents to the user a series of marker genotyping quality metrics. These include a check for conformance with Hardy–Weinberg equilibrium, a tally of Mendelian inheritance errors and the percentage of individuals successfully genotyped for that marker. The program filters out markers which fall below a preset threshold for these tests. The user can adjust these thresholds as well as handpick markers to add or remove from the subsequent steps. At any time later in the process, the user may return to this quality control panel, add or remove additional markers, and have the changes immediately reflected in the ongoing analyses.
Haploview calculates several pairwise measures of LD, which it uses to create a graphical representation (Fig. 1). The user has the option to select one of several commonly used block definitions (Gabriel et al., 2002; Wang et al., 2002) to partition the region into segments of strong LD. Alternatively, the user may manually select groups of markers for subsequent haplotype analysis. This view also allows a number of different color schemes to represent the LD relationships. Further, the program allows the display of an ‘analysis track’ above the LD plot, to display continuous variables such as recombination rate estimates (McVean et al., 2004) (Fig. 1).
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Once groups of markers are selected (either automatically or manually), the program generates haplotypes and their population frequencies (Fig. 1). This display shows lines to indicate transitions from one block to the next with frequency corresponding to the thickness of the line and also presents Hedrick's multiallelic D', which represents the degree of LD between two blocks, treating each haplotype within a block as an ‘allele’ of that region. Again, customization is available for nearly all aspects of the display, including displaying alleles as letters, numbers or colored boxes and displaying only those haplotypes above an adjustable threshold in the population.
If affection status is included in the input file, Haploview also calculates the standard TDT statistic (for trio data) or simple 
2 (for case/control data) for each marker that can be used for association studies. Future versions will include several haplotype-tag SNP selection methods as well as haplotype-based association testing and evaluation of significance using permutation testing. These final features allow the user to go from raw genotype data through exploring genetic associations in one easy to use software package. Haploview is maintained as an open source project (http://sourceforge.net/projects/haploview/), which allows external parties to add their own methods in addition to the continuing development by the authors.
Each of these views of the data is shown on a separate tab (Fig. 1), allowing the user to move from one to the next, with interactive modifications made by the user in any panel reflected in all the others. For example, one can return at any time to the review of marker quality and manually include or exclude individual markers—these changes are instantly reflected in the LD and haplotype panels. This provides the ability to analyze the data in real-time. The information on each panel is also able to be exported to a PNG for use in presentations or publications or dumped to a text file. Additionally, the program has a fully functional command-line mode, which allows users to run all the analyses without opening the GUI on one or more files at once.
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IMPLEMENTATION |
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Haploview is written entirely in Java, which means it is usable on any platform with Java 1.3 or later installed. Running on a 1.8 GHz Pentium 4 with 1 GB of RAM, Haploview can display a dataset with 200 markers genotyped in 400 individuals and adjust parameters with no noticeable delay. The program is also able to be used (from the command line) to do the LD calculations on very large datasets in comparatively small amounts of time. Haploview was able to compute 3.3 million pairwise LD values (comparisons of all markers closer than 500 KB in a 45 500 marker dataset) in 30 min.
Haploview uses a two marker EM (ignoring missing data) to estimate the maximum-likelihood values of the four gamete frequencies, from which the D', LOD and r 2 calculations derive. Haplotype phase and population frequency are inferred using a standard EM algorithm with a partition–ligation approach for blocks with greater than 10 markers. Conformance with Hardy–Weinberg equilibrium is computed using an exact test (G.Abecasis and J.Wigginton, personal communication).
Received on June 23, 2004; revised on July 23, 2004; accepted on July 23, 2004
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REFERENCES |
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TOPAbstractINTRODUCTIONFEATURESIMPLEMENTATIONREFERENCES |
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Daly, M.J., Rioux, J.D., Schaffner, S.F., Hudson, T.J., Lander, E.S. (2001) High-resolution haplotype structure in the human genome. Nat. Genet., 29, 229–232[CrossRef][Web of Science][Medline].
Gabriel, S.B., Schaffner, S.F., Nguyen, H., Moore, J.M., Roy, J., Blumenstiel, B., Higgins, J., Defelice, M., Lochner, A., Faggart, M., et al. (2002) The structure of haplotype blocks in the human genome. Science, 296, 2225–2229
Geesaman, B.J., Benson, E., Brewster, S.J., Kunkel, L.M., Blanche, H., Thomas, G., Perls, T.T., Daly, M.J., Puca, A.A. (2003) Haplotype-based identification of a microsomal transfer protein marker associated with the human lifespan. Proc. Natl Acad. Sci., USA, 100, 14115–20
The International HapMap Consortium. (2003) The International HapMap Project. Nature, 18, 789–796.
McVean, G.A., Myers, S.R., Hunt, S., Deloukas, P., Bentley, D.R., Donnelly, P. (2004) The fine-scale structure of recombination rate variation in the human genome. Science, 304, 581–584
Reich, D.E., Cargill, M., Bolk, S., Ireland, J., Sabeti, P.C., Richter, D.J., Lavery, T., Kouyoumjian, R., Farhadian, S.F., Ward, R., Lander, E.S. (2001) Linkage disequilibrium in the human genome. Nature, 411, 199–204[CrossRef][Medline].
Rioux, J.D., Daly, M.J., Silverberg, M.S., Lindblad, K., Steinhart, H., Cohen, Z., Delmonte, T., Kocher, K., Miller, K., Guschwan, S., et al. (2001) Genetic variation in the 5q31 cytokine gene cluster confers susceptibility to Crohn disease. Nat. Genet., 29, 223–228[CrossRef][Web of Science][Medline].
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Wang, N., Akey, J.M., Zhang, K., Chakraborty, R., Jin, L. (2002) Distribution of recombination crossovers and the origin of haplotype blocks: the interplay of population history, recombination, and mutation. Am. J. Hum. Genet., 71, 1227–1234[CrossRef][Web of Science][Medline].
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Y. Zhu, R. G. Stevens, A. E. Hoffman, L. M. FitzGerald, E. M. Kwon, E. A. Ostrander, S. Davis, T. Zheng, and J. L. Stanford Testing the Circadian Gene Hypothesis in Prostate Cancer: A Population-Based Case-Control Study Cancer Res., December 15, 2009; 69(24): 9315 - 9322. [Abstract] [Full Text] [PDF]
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 M. McGeachie, R. L. B. Ramoni, J. C. Mychaleckyj, K. L. Furie, J. M. Dreyfuss, Y. Liu, D. Herrington, X. Guo, J. A. Lima, W. Post, et al. Integrative Predictive Model of Coronary Artery Calcification in Atherosclerosis Circulation, December 15, 2009; 120(24): 2448 - 2454. [Abstract] [Full Text] [PDF]
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 M. Jagodic, C. Colacios, R. Nohra, A. S. Dejean, A. D. Beyeen, M. Khademi, A. Casemayou, L. Lamouroux, C. Duthoit, O. Papapietro, et al. A Role for VAV1 in Experimental Autoimmune Encephalomyelitis and Multiple Sclerosis Science Translational Medicine, December 9, 2009; 1(10): 10ra21 - 10ra21. [Abstract] [Full Text] [PDF]
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J. Hardin, Y. He, H. S. Javitz, J. Wessel, R. E. Krasnow, E. Tildesley, H. Hops, G. E. Swan, and A. W. Bergen Nicotine Withdrawal Sensitivity, Linkage to chr6q26, and Association of OPRM1 SNPs in the SMOking in FAMilies (SMOFAM) Sample Cancer Epidemiol. Biomarkers Prev., December 1, 2009; 18(12): 3399 - 3406. [Abstract] [Full Text] [PDF]
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P. Kiesler, A. Shakya, D. Tantin, and D. Vercelli An allergy-associated polymorphism in a novel regulatory element enhances IL13 expression Hum. Mol. Genet., December 1, 2009; 18(23): 4513 - 4520. [Abstract] [Full Text] [PDF]
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A. Tonjes, M. Koriath, D. Schleinitz, K. Dietrich, Y. Bottcher, N. W. Rayner, P. Almgren, B. Enigk, O. Richter, S. Rohm, et al. Genetic variation in GPR133 is associated with height: genome wide association study in the self-contained population of Sorbs Hum. Mol. Genet., December 1, 2009; 18(23): 4662 - 4668. [Abstract] [Full Text] [PDF]
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 P. Tejera, Z. Wang, R. Zhai, L. Su, C.-C. Sheu, D. M. Taylor, F. Chen, M. N. Gong, B. T. Thompson, and D. C. Christiani Genetic Polymorphisms of Peptidase Inhibitor 3 (Elafin) Are Associated with Acute Respiratory Distress Syndrome Am. J. Respir. Cell Mol. Biol., December 1, 2009; 41(6): 696 - 704. [Abstract] [Full Text] [PDF]
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S. Abhary, K. P. Burdon, A. Gupta, S. Lake, D. Selva, N. Petrovsky, and J. E. Craig Common Sequence Variation in the VEGFA Gene Predicts Risk of Diabetic Retinopathy Invest. Ophthalmol. Vis. Sci., December 1, 2009; 50(12): 5552 - 5558. [Abstract] [Full Text] [PDF]
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 E. Fisher, N. Stefan, K. Saar, D. Drogan, M. B. Schulze, A. Fritsche, H.-G. Joost, H.-U. Haring, N. Hubner, H. Boeing, et al. Association of AHSG Gene Polymorphisms With Fetuin-A Plasma Levels and Cardiovascular Diseases in the EPIC-Potsdam Study Circ Cardiovasc Genet, December 1, 2009; 2(6): 607 - 613. [Abstract] [Full Text] [PDF]
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S. Su, J. Zhao, J. D. Bremner, A. H. Miller, W. Tang, M. Bouzyk, H. Snieder, O. Novik, N. Afzal, J. Goldberg, et al. Serotonin Transporter Gene, Depressive Symptoms, and Interleukin-6 Circ Cardiovasc Genet, December 1, 2009; 2(6): 614 - 620. [Abstract] [Full Text] [PDF]
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M. R. Jones, R. Mathur, J. Cui, X. Guo, R. Azziz, and M. O. Goodarzi Independent Confirmation of Association between Metabolic Phenotypes of Polycystic Ovary Syndrome and Variation in the Type 6 17{beta}-Hydroxysteroid Dehydrogenase Gene J. Clin. Endocrinol. Metab., December 1, 2009; 94(12): 5034 - 5038. [Abstract] [Full Text] [PDF]
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 M. J. Prodoehl, N. Hatzirodos, H. F. Irving-Rodgers, Z. Z. Zhao, J. N. Painter, T. E. Hickey, M. A. Gibson, W. E. Rainey, B. R. Carr, H. D. Mason, et al. Genetic and gene expression analyses of the polycystic ovary syndrome candidate gene fibrillin-3 and other fibrillin family members in human ovaries Mol. Hum. Reprod., December 1, 2009; 15(12): 829 - 841. [Abstract] [Full Text] [PDF]
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 W.-H. Jia, Q.-H. Pan, H.-D. Qin, Y.-F. Xu, G.-P. Shen, L. Chen, L.-Z. Chen, Q.-S. Feng, M.-H. Hong, Y.-X. Zeng, et al. A Case-control and a family-based association study revealing an association between CYP2E1 polymorphisms and nasopharyngeal carcinoma risk in Cantonese Carcinogenesis, December 1, 2009; 30(12): 2031 - 2036. [Abstract] [Full Text] [PDF]
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 H. S. BACHMANN, H. RUBBEN, K. W. SCHMID, W. SIFFERT, and K. RIEMANN DNA Repair Gene XRCC1 Polymorphisms and Outcome of Renal Cell Carcinoma in Caucasian Patients Anticancer Res, December 1, 2009; 29(12): 5131 - 5135. [Abstract] [Full Text] [PDF]
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 E. M. Hill-Burns and A. G. Clark X-Linked Variation in Immune Response in Drosophila melanogaster Genetics, December 1, 2009; 183(4): 1477 - 1491. [Abstract] [Full Text] [PDF]
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L. Zuccolo, N. Fitz-Simon, R. Gray, S. M. Ring, K. Sayal, G. D. Smith, and S. J. Lewis A non-synonymous variant in ADH1B is strongly associated with prenatal alcohol use in a European sample of pregnant women Hum. Mol. Genet., November 15, 2009; 18(22): 4457 - 4466. [Abstract] [Full Text] [PDF]
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 P Tikka-Kleemola, M. Kaunisto, E Hamalainen, U Todt, H Gobel, J Kaprio, C Kubisch, M Farkkila, A Palotie, M Wessman, et al. Genetic Association Study of Endothelin-1 and Its Receptors EDNRA and EDNRB in Migraine with Aura Cephalalgia, November 1, 2009; 29(11): 1224 - 1231. [Abstract] [Full Text] [PDF]
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L. S.-H. Wu, C.-H. Hsieh, D. Pei, Y.-J. Hung, S.-W. Kuo, and E. Lin Association and interaction analyses of genetic variants in ADIPOQ, ENPP1, GHSR, PPAR{gamma} and TCF7L2 genes for diabetic nephropathy in a Taiwanese population with type 2 diabetes Nephrol. Dial. Transplant., November 1, 2009; 24(11): 3360 - 3366. [Abstract] [Full Text] [PDF]
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B. I. Freedman, P. J. Hicks, M. A. Bostrom, M. E. Comeau, J. Divers, A. J. Bleyer, J. B. Kopp, C. A. Winkler, G. W. Nelson, C. D. Langefeld, et al. Non-muscle myosin heavy chain 9 gene MYH9 associations in African Americans with clinically diagnosed type 2 diabetes mellitus-associated ESRD Nephrol. Dial. Transplant., November 1, 2009; 24(11): 3366 - 3371. [Abstract] [Full Text] [PDF]
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 B. K. Rana, J. Wessel, V. Mahboubi, F. Rao, J. Haeller, J. R. Gayen, E. Eskin, A. M. Valle, M. Das, S. K. Mahata, et al. Natural Variation within the Neuronal Nicotinic Acetylcholine Receptor Cluster on Human Chromosome 15q24: Influence on Heritable Autonomic Traits in Twin Pairs J. Pharmacol. Exp. Ther., November 1, 2009; 331(2): 419 - 428. [Abstract] [Full Text] [PDF]
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P.-a. B. Shih, L. Wang, S. Chiron, G. Wen, C. Nievergelt, M. Mahata, S. Khandrika, F. Rao, M. M. Fung, S. K. Mahata, et al. Peptide YY (PYY) Gene Polymorphisms in the 3'-Untranslated and Proximal Promoter Regions Regulate Cellular Gene Expression and PYY Secretion and Metabolic Syndrome Traits in Vivo J. Clin. Endocrinol. Metab., November 1, 2009; 94(11): 4557 - 4566. [Abstract] [Full Text] [PDF]
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K. Luotola, R. Paakkonen, M. Alanne, T. Lanki, L. Moilanen, I. Surakka, A. Pietila, M. Kahonen, M. S. Nieminen, Y. A. Kesaniemi, et al. Association of Variation in the Interleukin-1 Gene Family with Diabetes and Glucose Homeostasis J. Clin. Endocrinol. Metab., November 1, 2009; 94(11): 4575 - 4583. [Abstract] [Full Text] [PDF]
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L. Chen, G. Davey Smith, D. M. Evans, A. Cox, D. A. Lawlor, J. Donovan, W. Yuan, I. N. M. Day, R. M. Martin, A. Lane, et al. Genetic Variants in the Vitamin D Receptor Are Associated with Advanced Prostate Cancer at Diagnosis: Findings from the Prostate Testing for Cancer and Treatment Study and a Systematic Review Cancer Epidemiol. Biomarkers Prev., November 1, 2009; 18(11): 2874 - 2881. [Abstract] [Full Text] [PDF]
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J. S. Kwon, Y. H. Joo, H. J. Nam, M. Lim, E.-Y. Cho, M. H. Jung, J.-S. Choi, B. Kim, D.-H. Kang, S. Oh, et al. Association of the Glutamate Transporter Gene SLC1A1 With Atypical Antipsychotics-Induced Obsessive-compulsive Symptoms Arch Gen Psychiatry, November 1, 2009; 66(11): 1233 - 1241. [Abstract] [Full Text] [PDF]
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 Y.-Y. Teo, X. Sim, R. T.H. Ong, A. K.S. Tan, J. Chen, E. Tantoso, K. S. Small, C.-S. Ku, E. J.D. Lee, M. Seielstad, et al. Singapore Genome Variation Project: A haplotype map of three Southeast Asian populations Genome Res., November 1, 2009; 19(11): 2154 - 2162. [Abstract] [Full Text] [PDF]
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 F.-I Hsieh, W.-C. Lo, H.-J. Lin, Y.-C. Hsieh, L.-M. Lien, C.-H. Bai, H.-P. Tseng, and H.-Y. Chiou Significant Synergistic Effect of Peroxisome Proliferator-Activated Receptor {gamma} C-2821T and Diabetes on the Risk of Ischemic Stroke Diabetes Care, November 1, 2009; 32(11): 2033 - 2035. [Abstract] [Full Text] [PDF]
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A. Eberlein, A. Takasuga, K. Setoguchi, R. Pfuhl, K. Flisikowski, R. Fries, N. Klopp, R. Furbass, R. Weikard, and C. Kuhn Dissection of Genetic Factors Modulating Fetal Growth in Cattle Indicates a Substantial Role of the Non-SMC Condensin I Complex, Subunit G (NCAPG) Gene Genetics, November 1, 2009; 183(3): 951 - 964. [Abstract] [Full Text] [PDF]
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 U Huffmeier, J Lascorz, T Becker, F Schurmeier-Horst, A Magener, A B Ekici, S Endele, C T Thiel, S Thoma-Uszynski, R Mossner, et al. Characterisation of psoriasis susceptibility locus 6 (PSORS6) in patients with early onset psoriasis and evidence for interaction with PSORS1 J. Med. Genet., November 1, 2009; 46(11): 736 - 744. [Abstract] [Full Text] [PDF]
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Y. Xue, X. Zhang, N. Huang, A. Daly, C. J. Gillson, D. G. MacArthur, B. Yngvadottir, A. C. Nica, C. Woodwark, Y. Chen, et al. Population Differentiation as an Indicator of Recent Positive Selection in Humans: An Empirical Evaluation Genetics, November 1, 2009; 183(3): 1065 - 1077. [Abstract] [Full Text] [PDF]
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D. A. Brown, F. Lindmark, P. Stattin, K. Balter, H.-O. Adami, S. L. Zheng, J. Xu, W. B. Isaacs, H. Gronberg, S. N. Breit, et al. Macrophage Inhibitory Cytokine 1: A New Prognostic Marker in Prostate Cancer Clin. Cancer Res., November 1, 2009; 15(21): 6658 - 6664. [Abstract] [Full Text] [PDF]
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 A-K Abelson, A M Delgado-Vega, S V Kozyrev, E Sanchez, R Velazquez-Cruz, N Eriksson, J Wojcik, M V P Linga Reddy, G Lima, S D'Alfonso, et al. STAT4 associates with systemic lupus erythematosus through two independent effects that correlate with gene expression and act additively with IRF5 to increase risk Ann Rheum Dis, November 1, 2009; 68(11): 1746 - 1753. [Abstract] [Full Text] [PDF]
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M. Ogorelkova, A. Navarro, F. Vivarelli, A. Ramirez-Soriano, and X. Estivill Positive Selection and Gene Conversion Drive the Evolution of a Brain-Expressed snoRNAs Cluster Mol. Biol. Evol., November 1, 2009; 26(11): 2563 - 2571. [Abstract] [Full Text] [PDF]
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H. J. Edenberg and Y. Liu Laboratory Methods for High-Throughput Genotyping CSH Protocols, November 1, 2009; 2009(11): pdb.top62 - pdb.top62. [Abstract] [Full Text]
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 M. Iijima, M. Tomita, S. Morozumi, Y. Kawagashira, T. Nakamura, H. Koike, M. Katsuno, N. Hattori, F. Tanaka, M. Yamamoto, et al. Single nucleotide polymorphism of TAG-1 influences IVIg responsiveness of Japanese patients with CIDP Neurology, October 27, 2009; 73(17): 1348 - 1352. [Abstract] [Full Text] [PDF]
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A. Hussein, E. Askar, M. Elsaeid, and F. Schaefer Functional polymorphisms in transforming growth factor-beta-1 (TGF{beta}-1) and vascular endothelial growth factor (VEGF) genes modify risk of renal parenchymal scarring following childhood urinary tract infection Nephrol. Dial. Transplant., October 26, 2009; (2009) gfp532v1. [Abstract] [Full Text] [PDF]
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 D. Voora, S. H. Shah, I. Spasojevic, S. Ali, C. R. Reed, B. A. Salisbury, and G. S. Ginsburg The SLCO1B1*5 genetic variant is associated with statin-induced side effects. J. Am. Coll. Cardiol., October 20, 2009; 54(17): 1609 - 1616. [Abstract] [Full Text] [PDF]
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M. R. Akbari, R. Malekzadeh, R. Shakeri, D. Nasrollahzadeh, M. Foumani, Y. Sun, A. Pourshams, A. Sadjadi, E. Jafari, M. Sotoudeh, et al. Candidate Gene Association Study of Esophageal Squamous Cell Carcinoma in a High-Risk Region in Iran Cancer Res., October 15, 2009; 69(20): 7994 - 8000. [Abstract] [Full Text] [PDF]
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 S. Cha, I. Koo, B. L. Park, S. Jeong, S. M. Choi, K. S. Kim, H. D. Shin, and J. Y. Kim Genetic Effects of FTO and MC4R Polymorphisms on Body Mass in Constitutional Types Evid. Based Complement. Altern. Med., October 11, 2009; (2009) nep162v1. [Abstract] [Full Text] [PDF]
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A. D. Johnson Single-Nucleotide Polymorphism Bioinformatics: A Comprehensive Review of Resources Circ Cardiovasc Genet, October 1, 2009; 2(5): 530 - 536. [Full Text] [PDF]
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M. T. Vuong, S. Lundberg, I. Gunnarsson, L. Wramner, M. Seddighzadeh, M. Hahn-Zoric, A. Fernstrom, L. A Hanson, L. T. Do, S. H. Jacobson, et al. Genetic variation in the transforming growth factor-{beta}1 gene is associated with susceptibility to IgA nephropathy Nephrol. Dial. Transplant., October 1, 2009; 24(10): 3061 - 3067. [Abstract] [Full Text] [PDF]
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 J. Y. Dai, M. Leblanc, N. L. Smith, B. Psaty, and C. Kooperberg SHARE: an adaptive algorithm to select the most informative set of SNPs for candidate genetic association Biostat., October 1, 2009; 10(4): 680 - 693. [Abstract] [Full Text] [PDF]
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Y.-H. Shu, J. Hartiala, A. H. Xiang, E. Trigo, J. M. Lawrence, H. Allayee, T. A. Buchanan, N. Bottini, and R. M. Watanabe Evidence for Sex-Specific Associations between Variation in Acid Phosphatase Locus 1 (ACP1) and Insulin Sensitivity in Mexican-Americans J. Clin. Endocrinol. Metab., October 1, 2009; 94(10): 4094 - 4102. [Abstract] [Full Text] [PDF]
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S. C. Body, C. D. Collard, S. K. Shernan, A. A. Fox, K.-Y. Liu, M. D. Ritchie, T. E. Perry, J. D. Muehlschlegel, S. Aranki, B. S. Donahue, et al. Variation in the 4q25 Chromosomal Locus Predicts Atrial Fibrillation After Coronary Artery Bypass Graft Surgery Circ Cardiovasc Genet, October 1, 2009; 2(5): 499 - 506. [Abstract] [Full Text] [PDF]
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I. Iatan, Z. Dastani, R. Do, D. Weissglas-Volkov, I. Ruel, J. C. Lee, A. Huertas-Vazquez, M.-R. Taskinen, A. Prat, N. G. Seidah, et al. Genetic Variation at the Proprotein Convertase Subtilisin/Kexin Type 5 Gene Modulates High-Density Lipoprotein Cholesterol Levels Circ Cardiovasc Genet, October 1, 2009; 2(5): 467 - 475. [Abstract] [Full Text] [PDF]
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S. Weinsheimer, H. Kim, L. Pawlikowska, Y. Chen, M. T. Lawton, S. Sidney, P.-Y. Kwok, C. E. McCulloch, and W. L. Young EPHB4 Gene Polymorphisms and Risk of Intracranial Hemorrhage in Patients With Brain Arteriovenous Malformations Circ Cardiovasc Genet, October 1, 2009; 2(5): 476 - 482. [Abstract] [Full Text] [PDF]
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E. L. Barry, L. B. Sansbury, M. V. Grau, I. U. Ali, S. Tsang, D. J. Munroe, D. J. Ahnen, R. S. Sandler, F. Saibil, J. Gui, et al. Cyclooxygenase-2 Polymorphisms, Aspirin Treatment, and Risk for Colorectal Adenoma Recurrence--Data from a Randomized Clinical Trial Cancer Epidemiol. Biomarkers Prev., October 1, 2009; 18(10): 2726 - 2733. [Abstract] [Full Text] [PDF]
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