130,809 research outputs found
Simultaneous Analysis of All SNPs in Genome-Wide and Re-Sequencing Association Studies
Get PDFTesting one SNP at a time does not fully realise the potential of genome-wide association studies to identify multiple causal variants, which is a plausible scenario for many complex diseases. We show that simultaneous analysis of the entire set of SNPs from a genome-wide study to identify the subset that best predicts disease outcome is now feasible, thanks to developments in stochastic search methods. We used a Bayesian-inspired penalised maximum likelihood approach in which every SNP can be considered for additive, dominant, and recessive contributions to disease risk. Posterior mode estimates were obtained for regression coefficients that were each assigned a prior with a sharp mode at zero. A non-zero coefficient estimate was interpreted as corresponding to a significant SNP. We investigated two prior distributions and show that the normal-exponential-gamma prior leads to improved SNP selection in comparison with single-SNP tests. We also derived an explicit approximation for type-I error that avoids the need to use permutation procedures. As well as genome-wide analyses, our method is well-suited to fine mapping with very dense SNP sets obtained from re- sequencing and/or imputation. It can accommodate quantitative as well as case-control phenotypes, covariate adjustment, and can be extended to search for interactions. Here, we demonstrate the power and empirical type-I error of our approach using simulated case-control data sets of up to 500 K SNPs, a real genome-wide data set of 300 K SNPs, and a sequence-based dataset, each of which can be analysed in a few hours on a desktop workstation
Genome-wide significance for dense SNP and resequencing data.
No full textThe problem of multiple testing is an important aspect of genome-wide association studies, and will become more important as marker densities increase. The problem has been tackled with permutation and false discovery rate procedures and with Bayes factors, but each approach faces difficulties that we briefly review. In the current context of multiple studies on different genotyping platforms, we argue for the use of truly genome-wide significance thresholds, based on all polymorphisms whether or not typed in the study. We approximate genome-wide significance thresholds in contemporary West African, East Asian and European populations by simulating sequence data, based on all polymorphisms as well as for a range of single nucleotide polymorphism (SNP) selection criteria. Overall we find that significance thresholds vary by a factor of >20 over the SNP selection criteria and statistical tests that we consider and can be highly dependent on sample size. We compare our results for sequence data to those derived by the HapMap Consortium and find notable differences which may be due to the small sample sizes used in the HapMap estimate
Balding DPCs are more senescent than sex-, age-, and site-matched non-balding DPCs.
No full text<p>(A) Non-balding DPCs isolated from the frontal scalp of normal individuals exhibited a relatively normal appearance at passage 2 compared with balding DPCs isolated from the frontal scalp of AGA patients of the same passage, which exhibited an enlarged, irregular, and flattened morphology. (B) SA-β-Gal activity was increased in balding DPCs. Scale bar = 100 µm. (C) Quantification of SA-β-Gal activity showed that the percentage of SA-β-Gal expression was increased in balding DPCs in all matched-pairs. (D) Balding DPCs exhibited an increase in cell size. (E) Prolongation of the cell doubling time were observed in balding DPCs. The pair 1–4 of the x axis in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079434#pone-0079434-g001" target="_blank">Figure 1C,D,E</a> means the each age (20, 24, 27 and 40 years), sex (male), site (frontal) matched pairs of normal control (non-AGA males) and AGA patient. Values are means ± SDs from three determinations per experiment from three independent experiments using second-passage DPCs (*<i>P</i><0.05, **<i>P</i><0.01 compared with matched controls).</p
Fregene: Simulation of realistic sequence-level data in populations and ascertained samples
Get PDFBackground: FREGENE simulates sequence-level data over large genomic regions in large populations. Because, unlike coalescent simulators, it works forwards through time, it allows complex scenarios of selection, demography, and recombination to be modelled simultaneously. Detailed tracking of sites under selection is implemented in FREGENE and provides the opportunity to test theoretical predictions and gain new insights into mechanisms of selection. We describe here main functionalities of both FREGENE and SAMPLE, a companion program that can replicate association study datasets.Results: We report detailed analyses of six large simulated datasets that we have made publicly available. Three demographic scenarios are modelled: one panmictic, one substructured with migration, and one complex scenario that mimics the principle features of genetic variation in major worldwide human populations. For each scenario there is one neutral simulation, and one with a complex pattern of selection.Conclusion: FREGENE and the simulated datasets will be valuable for assessing the validity of models for selection, demography and population genetic parameters, as well as the efficacy of association studies. Its principle advantages are modelling flexibility and computational efficiency. It is open source and object-oriented. As such, it can be customised and the range of models extended
Modelling admixture and extracting information about linkage that is generated by admixture from marker genotypes
Get PDFAssociation of African genetic admixture with resting metabolic rate and obesity among women.
No full textOBJECTIVE: To investigate the role of genetic admixture in explaining phenotypic variation in obesity-related traits in a sample of African-American women (n = 145) and to determine significant associations between obesity traits and admixture genetic markers. RESEARCH METHODS AND PROCEDURES: Associations between genetic admixture and BMI, resting metabolic rate, fat mass, fat-free mass, and bone mineral density were tested using linear regression considering the estimation of admixture by 1) a maximum-likelihood approach (MLA) and 2) a Bayesian analysis. RESULTS: Both the conservative MLA and the Bayesian approach support an association between African genetic admixture and BMI. Evidence for the associations of African genetic admixture with fat mass and fat-free mass was supported by the Bayesian analysis; the MLA supported an association with bone mineral density. When the individual ancestry informative markers that were used to estimate admixture were tested for associations with BMI, significant associations were identified in chromosomes 1, 11, and 12. DISCUSSION: These results provide evidence supporting the application of admixture mapping methods to the identification of genes that result in higher levels of obesity among African-American women. Further research is needed to replicate and further explore these findings
Admixture in the Hispanics of the San Luis Valley, Colorado, and its implications for complex trait gene mapping
Get PDFHispanic populations are a valuable resource that can and should facilitate the identification of complex trait genes by means of admixture mapping (AM). In this paper we focus on a particular Hispanic population living in the San Luis Valley (SLV) in Southern Colorado.We used a set of 22 Ancestry Informative Markers (AIMs) to describe the admixture process and dynamics in this population. AIMs are defined as genetic markers that exhibit allele frequency differences between parental populations ≥30%, and are more informative for studying admixed populations than random markers. The ancestral proportions of the SLV Hispanic population are estimated as 62.7 ± 2.1% European, 34.1 ± 1.9% Native American and 3.2 ± 1.5% West African. We also estimated the ancestral proportions of individuals using these AIMs. Population structure was demonstrated by the excess association of unlinked markers, the correlation between estimates of admixture based on unlinked marker sets, and by a highly significant correlation between individual Native American ancestry and skin pigmentation (R 2 = 0.082, p < 0.001). We discuss the implications of these findings in disease gene mapping efforts.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65937/1/j.1529-8817.2003.00084.x.pd
Relation of type 2 diabetes to individual admixture and candidate gene polymorphisms in the Hispanic American population of San Luis Valley, Colorado.
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Bivariate kurtotic distributions of garment fibre data
No full textA bivariate and unimodal distribution is introduced to model an unconventionally distributed data set collected by the Forensic Science Service. This family of distributions allows for a different kurtosis in each orthogonal direction and has a constructive rather than probability density function definition, making conventional inference impossible. However, the construction and inference work well with a Bayesian Markov chain Monte Carlo analysis
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