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Genome-Wide Association Study on the Development of Cross-Reactive Neutralizing Antibodies in HIV-1 Infected Individuals  [PDF]
Zelda Euler, Marit J. van Gils, Brigitte D. Boeser-Nunnink, Hanneke Schuitemaker, Dani?lle van Manen
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0054684
Abstract: Broadly neutralizing antibodies may protect against HIV-1 acquisition. In natural infection, only 10–30% of patients have cross-reactive neutralizing humoral immunity which may relate to viral and or host factors. To explore the role of host genetic markers in the formation of cross-reactive neutralizing activity (CrNA) in HIV-1 infected individuals, we performed a genome-wide association study (GWAS), in participants of the Amsterdam Cohort Studies with known CrNA in their sera. Single-nucleotide polymorphisms (SNPs) with the strongest P-values are located in the major histocompatibility complex (MHC) region, close to MICA (P = 7.68×10?7), HLA-B (P = 6.96×10?6) and in the coding region of HCP5 (P = 1.34×10?5). However, none of the signals reached genome-wide significance. Our findings underline the potential involvement of genes close or within the MHC region with the development of CrNA.
Introduction to the Special Issue: Genome-Wide Association Studies  [PDF]
Gang Zheng,Jonathan Marchini,Nancy L. Geller
Statistics , 2010, DOI: 10.1214/09-STS310
Abstract: Introduction to the Special Issue: Genome-Wide Association Studies
Replication in Genome-Wide Association Studies  [PDF]
Peter Kraft,Eleftheria Zeggini,John P. A. Ioannidis
Statistics , 2010, DOI: 10.1214/09-STS290
Abstract: Replication helps ensure that a genotype-phenotype association observed in a genome-wide association (GWA) study represents a credible association and is not a chance finding or an artifact due to uncontrolled biases. We discuss prerequisites for exact replication, issues of heterogeneity, advantages and disadvantages of different methods of data synthesis across multiple studies, frequentist vs. Bayesian inferences for replication, and challenges that arise from multi-team collaborations. While consistent replication can greatly improve the credibility of a genotype-phenotype association, it may not eliminate spurious associations due to biases shared by many studies. Conversely, lack of replication in well-powered follow-up studies usually invalidates the initially proposed association, although occasionally it may point to differences in linkage disequilibrium or effect modifiers across studies.
Power analysis for genome-wide association studies
Robert J Klein
BMC Genetics , 2007, DOI: 10.1186/1471-2156-8-58
Abstract: The power of genome-wide association studies can be computed using a set of tag SNPs and a large number of genotyped SNPs in a representative population, such as available through the HapMap project. As expected, power increases with increasing sample size and effect size. Power also depends on the tag SNPs selected. In some cases, more power is obtained by genotyping more individuals at fewer SNPs than fewer individuals at more SNPs.Genome-wide association studies should be designed thoughtfully, with the choice of genotyping platform and sample size being determined from careful power calculations.One goal of modern human genetics is to identify the genetic variants that predispose individuals to develop common, complex diseases. It has been proposed that population-based association studies will be more powerful than traditional family-based linkage methods in identifying such high-frequency, low-penetrance alleles [1]. Such studies require the genotypes a large number of polymorphisms (usually single nucleotide polymorphisms [SNPs]) across the genome, each of which is tested for association with the phenotype of interest. As originally proposed, this would be a direct test of association, in which the functional mutation is presumed to be genotyped. An alternate approach to association studies takes advantage of the correlation between SNPs, called linkage disequilibrium (LD), that can occur due to the genealogical history of the polymorphisms [2]. In this approach, often called indirect association, one SNP is genotyped and used to infer indirectly the genotypes at other SNPs with which it is in high LD [3]. As one genotyped SNP, called a "tag" SNP, can be in LD with numerous other SNPs, much fewer SNPs (105 – 106) would need to be genotyped to capture the common variation in the genome [3]. Recent advances in genotyping technology make such studies feasible [4,5] and the first results of such studies are being published [6-10].One key question in designing suc
Chapter 11: Genome-Wide Association Studies  [PDF]
William S. Bush ,Jason H. Moore
PLOS Computational Biology , 2012, DOI: 10.1371/journal.pcbi.1002822
Abstract: Genome-wide association studies (GWAS) have evolved over the last ten years into a powerful tool for investigating the genetic architecture of human disease. In this work, we review the key concepts underlying GWAS, including the architecture of common diseases, the structure of common human genetic variation, technologies for capturing genetic information, study designs, and the statistical methods used for data analysis. We also look forward to the future beyond GWAS.
An Analysis Pipeline for Genome-wide Association Studies
Stefan Stefanov,James Lautenberger,Bert Gold
Cancer Informatics , 2008,
Abstract: We developed an efficient pipeline to analyze genome-wide association study single nucleotide polymorphism scan results. Perl scripts were used to convert genotypes called using the BRLMM algorithm into a modified PB format. We computed summary statistics characteristic of our case and control populations including allele counts, missing values, heterozygosity, measures of compliance with Hardy-Weinberg equilibrium, and several population difference statistics. In addition, we computed association tests, including exact tests of association for genotypes, alleles, the Cochran-Armitage linear trend test, and dominant, recessive, and overdominant models at every single nucleotide polymorphism (SNP). In addition, pairwise linkage disequilbrium statistics were elaborated, using the command line version of HaploView, which was possible by writing a reformatting script. Additional Perl scripts permit loading the results into a MySQL database conjoined with a Generic Genome Browser (gbrowse) for comprehensive visualization. This browser incorporates a download feature that provides actual case and control genotypes to users in associated genomic regions. Thus, re-analysis “on the y” is possible for casual browser users from anywhere on the Internet.
Musings on genome medicine: genome wide association studies
David G Nathan, Stuart H Orkin
Genome Medicine , 2009, DOI: 10.1186/gm3
Abstract: The development of practical approaches to DNA sequencing in the 1990s produced a remarkable scientific challenge - a proposal to establish the complete (or near complete) sequence of the human genome. Although most members of the scientific community and the media hailed the 2001 announcement of the project's initial success [1,2] as a huge intellectual and technical breakthrough, there were other voices [3]. One of us (SHO) was a member of the original US National Research Council panel that evaluated the proposal. The panel was initially highly skeptical but ended its deliberations with unbridled enthusiasm. Some leading scientists grumbled that the genome project, as it was called, was a quagmire and a money sump that had drained funds from individual investigators and provided a jumble of DNA bases the sequences of which would shed very little light on the human condition. The naysayers particularly emphasized their doubts that any medical benefit would be derived from most of the data. Indeed, when most of the human DNA sequence data had been collected, the laboratories that had accomplished the feat began to use their considerable resources to sequence the DNA of one animal species after another [4,5], with the questionable assumption that knowledge of DNA evolution would be useful and not a mere intellectual and technical exercise. Doubters began to wonder whether a large proportion of the biomedical research budget would be wasted in an effort to keep sequencing machines humming. The doubts were, in fact, quite loud in some quarters, despite the obvious fact that the project has provided investigators with ready access to all genes and facilitated positional cloning (see below).Responding to the criticism, and always ebulliently optimistic, Francis Collins, the guiding spirit of the public effort to sequence the human genome, simply changed the subject. He proposed the human HapMap project [6] to replace laborious and relatively crude restriction enzyme map
Genome-wide association studies in Plasmodium species
Bridget Penman, Caroline Buckee, Sunetra Gupta, Sean Nee
BMC Biology , 2010, DOI: 10.1186/1741-7007-8-90
Abstract: See research article http://www.biomedcentral.com/1471-2156/11/65 webciteSince the publication of the complete human genome sequence in 2003, hundreds of genome-wide association studies (GWAS) have been carried out in the human population to identify polymorphisms associated with human disease [1,2]. As more genome sequences are published, including those of many important human pathogens, there is an expectation that GWAS will also provide insights into the evolution of pathogen virulence or drug resistance.In a recent study published in BMC Genetics, Orjuela-Sanchéz et al. [3] present an assessment of the feasibility of future GWAS in the malaria parasite Plasmodium vivax. They analyzed a 100-kb chromosome segment (0.4% of the parasite genome) in field samples of the parasite from South America and Asia with the aim of determining the genetic diversity in these populations and to look for geographical effects. The authors found that the Brazilian vivax population they studied was amenable to future GWAS as it contained high levels of genetic diversity - a prerequisite for distinguishing the areas of the parasite genome associated with traits of interest. They also confirmed that it exhibits appropriate levels of linkage disequilibrium - the non-random association of specific genetic markers with the trait of interest, indicating that the marker is in or near a gene that underlies that trait. Too little linkage disequilibrium means that a genetic marker is unlikely to stay associated with the gene that causes the trait of interest; too much and there is a risk of 'false positives' where the marker appears correlated with a trait of interest but is actually far away from the gene that governs it. The authors raise several notes of caution, however, not least the fact that substantial geographical substructuring exists in vivax populations, which could confound efforts to find true associations between markers and traits. The authors rightly emphasize the need for ca
Progress of genome wide association study in domestic animals  [cached]
Zhang Hui,Wang Zhipeng,Wang Shouzhi,Li Hui
Journal of Animal Science and Biotechnology , 2012, DOI: 10.1186/2049-1891-3-26
Abstract: Domestic animals are invaluable resources for study of the molecular architecture of complex traits. Although the mapping of quantitative trait loci (QTL) responsible for economically important traits in domestic animals has achieved remarkable results in recent decades, not all of the genetic variation in the complex traits has been captured because of the low density of markers used in QTL mapping studies. The genome wide association study (GWAS), which utilizes high-density single-nucleotide polymorphism (SNP), provides a new way to tackle this issue. Encouraging achievements in dissection of the genetic mechanisms of complex diseases in humans have resulted from the use of GWAS. At present, GWAS has been applied to the field of domestic animal breeding and genetics, and some advances have been made. Many genes or markers that affect economic traits of interest in domestic animals have been identified. In this review, advances in the use of GWAS in domestic animals are described.
Estimating Reproducibility in Genome-Wide Association Studies  [PDF]
Wei Jiang,Jing-Hao Xue,Weichuan Yu
Quantitative Biology , 2015,
Abstract: Genome-wide association studies (GWAS) are widely used to discover genetic variants associated with diseases. To control false positives, all findings from GWAS need to be verified with additional evidences, even for associations discovered from a high power study. Replication study is a common verification method by using independent samples. An association is regarded as true positive with a high confidence when it can be identified in both primary study and replication study. Currently, there is no systematic study on the behavior of positives in the replication study when the positive results of primary study are considered as the prior information. In this paper, two probabilistic measures named Reproducibility Rate (RR) and False Irreproducibility Rate (FIR) are proposed to quantitatively describe the behavior of primary positive associations (i.e. positive associations identified in the primary study) in the replication study. RR is a conditional probability measuring how likely a primary positive association will also be positive in the replication study. This can be used to guide the design of replication study, and to check the consistency between the results of primary study and those of replication study. FIR, on the contrary, measures how likely a primary positive association may still be a true positive even when it is negative in the replication study. This can be used to generate a list of potentially true associations in the irreproducible findings for further scrutiny. The estimation methods of these two measures are given. Simulation results and real experiments show that our estimation methods have high accuracy and good prediction performance.
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