139 research outputs found

    Fast individual ancestry inference from DNA sequence data leveraging allele frequencies for multiple populations.

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    BackgroundEstimation of individual ancestry from genetic data is useful for the analysis of disease association studies, understanding human population history and interpreting personal genomic variation. New, computationally efficient methods are needed for ancestry inference that can effectively utilize existing information about allele frequencies associated with different human populations and can work directly with DNA sequence reads.ResultsWe describe a fast method for estimating the relative contribution of known reference populations to an individual's genetic ancestry. Our method utilizes allele frequencies from the reference populations and individual genotype or sequence data to obtain a maximum likelihood estimate of the global admixture proportions using the BFGS optimization algorithm. It accounts for the uncertainty in genotypes present in sequence data by using genotype likelihoods and does not require individual genotype data from external reference panels. Simulation studies and application of the method to real datasets demonstrate that our method is significantly times faster than previous methods and has comparable accuracy. Using data from the 1000 Genomes project, we show that estimates of the genome-wide average ancestry for admixed individuals are consistent between exome sequence data and whole-genome low-coverage sequence data. Finally, we demonstrate that our method can be used to estimate admixture proportions using pooled sequence data making it a valuable tool for controlling for population stratification in sequencing based association studies that utilize DNA pooling.ConclusionsOur method is an efficient and versatile tool for estimating ancestry from DNA sequence data and is available from https://sites.google.com/site/vibansal/software/iAdmix

    Railway bridge over a local brook

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    Předmětem práce bylo navrhnout přemostění místní vodoteče pro převedení jednokolejné železniční trati. Z možných variant se zabývá konstrukcí předpjatého trámového mostu o jednom poli s dolní mostovkou. Cílem této práce bylo navrhnout a posoudit nosnou konstrukci na základě mezních stavů únosnosti a mezních stavů použitelnosti dle platných norem EN.The purpose of this work was to design a bridge local stream to convert single-track railway line. The possible variation deals with the construction of prestressed girder bridge on one field with the lower deck. The aim of this work was to design and evaluate the structure on the basis of ultimate limit states and serviceability limit states according to applicable EN standards.

    Simulation-based homozygosity mapping with the GAW14 COGA dataset on alcoholism

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    BACKGROUND: We have developed a simulation-based approach to the analysis of shared homozygous chromosomal segments and have applied it to data on allele sharing among alcoholics in a single Collaborative Study on the Genetics of Alcoholism pedigree. Our assessment of sharing involved the use of a single-nucleotide polymorphism (SNP) marker map provided by Affymetrix. RESULTS: All 11 affected individuals in the selected pedigree shared 2 copies of an allele at 4 adjacent SNPs in a region on chromosome 5. Via simulation, we determined that the probability that such sharing is caused by mere chance is less than 0.0000001. After correcting for undocumented inbreeding, this probability rose to 0.0016. The probability that the shared segment emanates from a single ancestor and is unrelated to the affection status is less than 0.0000001 in the corrected pedigree. Haplotype association analysis and a search for a protective locus using unaffected individuals yielded no significant results. CONCLUSION: Homozygosity mapping results on chromosome 5 provide suggestive evidence of the region's role as one that may harbor a genetic determinant of alcoholism. Furthermore, the probabilities of chance homozygous allele sharing for the original and for the inbreeding-corrected pedigree provide insight into the impact that inbreeding can have on such calculations

    Pedestrian bridge across the river Labe

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    Předmětem práce byl návrh přemostění řeky Labe v Hradci Králové za účelem převedení cyklistické a pěší dopravy mezi břehy. Toto bylo navrhnuto ve třech variantách provedení. Pro podrobnější řešení byla vybrána varianta půdorysně zakřivené dvouramenné obloukové konstrukce. Cílem práce bylo navrhnout a posoudit nosnou konstrukci lávky na základě mezních stavů únosnosti a mezních stavů použitelnosti dle platných norem EC.The thesis deals with a design of the river Labe bridging in the city Hradec Kralove. In order to make option for cyclists and pedistrians to cross between shores. There were made three design variants. For detailed solution curved twin-arm arched structure was chosen. The aim of the thesis was design and assessment of Bering strucutre of the footbridge according ultimate limit states and serviceability limit state given by valid Eurocodes.

    Generalized Analysis of Molecular Variance

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    Many studies in the fields of genetic epidemiology and applied population genetics are predicated on, or require, an assessment of the genetic background diversity of the individuals chosen for study. A number of strategies have been developed for assessing genetic background diversity. These strategies typically focus on genotype data collected on the individuals in the study, based on a panel of DNA markers. However, many of these strategies are either rooted in cluster analysis techniques, and hence suffer from problems inherent to the assignment of the biological and statistical meaning to resulting clusters, or have formulations that do not permit easy and intuitive extensions. We describe a very general approach to the problem of assessing genetic background diversity that extends the analysis of molecular variance (AMOVA) strategy introduced by Excoffier and colleagues some time ago. As in the original AMOVA strategy, the proposed approach, termed generalized AMOVA (GAMOVA), requires a genetic similarity matrix constructed from the allelic profiles of individuals under study and/or allele frequency summaries of the populations from which the individuals have been sampled. The proposed strategy can be used to either estimate the fraction of genetic variation explained by grouping factors such as country of origin, race, or ethnicity, or to quantify the strength of the relationship of the observed genetic background variation to quantitative measures collected on the subjects, such as blood pressure levels or anthropometric measures. Since the formulation of our test statistic is rooted in multivariate linear models, sets of variables can be related to genetic background in multiple regression-like contexts. GAMOVA can also be used to complement graphical representations of genetic diversity such as tree diagrams (dendrograms) or heatmaps. We examine features, advantages, and power of the proposed procedure and showcase its flexibility by using it to analyze a wide variety of published data sets, including data from the Human Genome Diversity Project, classical anthropometry data collected by Howells, and the International HapMap Project

    DNA variation and brain region-specific expression profiles exhibit different relationships between inbred mouse strains: implications for eQTL mapping studies

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    BACKGROUND: Expression quantitative trait locus (eQTL) mapping is used to find loci that are responsible for the transcriptional activity of a particular gene. In recent eQTL studies, expression profiles were derived from either homogenized whole brain or collections of large brain regions. However, the brain is a very heterogeneous organ, and expression profiles of different brain regions vary significantly. Because of the importance and potential power of eQTL studies in identifying regulatory networks, we analyzed gene expression patterns in different brain regions from multiple inbred mouse strains and investigated the implications for the design and analysis of eQTL studies. RESULTS: Gene expression profiles of five brain regions in six inbred mouse strains were studied. Few genes exhibited a significant strain-specific expression pattern, whereas a large number of genes exhibited brain region-specific patterns. We constructed phylogenetic trees based on the expression relationships between the strains and compared them with a DNA-level relationship tree. The trees based on the expression of strain-specific genes were constant across brain regions and mirrored DNA-level variation. However, the trees based on region-specific genes exhibited a different set of strain relationships, depending on the brain region. An eQTL analysis showed enrichment of cis-acting regulators among strain-specific genes, whereas brain region-specific genes appear to be mainly regulated by trans-acting elements. CONCLUSION: Our results suggest that many regulatory networks are highly brain region specific and indicate the importance of conducting eQTL mapping studies using data from brain regions or tissues that are physiologically and phenotypically relevant to the trait of interest

    The interrelation of needs and quality of life in first-episode schizophrenia

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    The interrelation between needs for care and quality of life has been described and replicated by several studies. The present work aims to add to the understanding of longitudinal interrelations between needs for care, quality of life, and other outcome measures by analyzing a sample of patients at the onset of schizophrenia. This study relied on data from the EUFEST trial, designed to compare first- and second-generation antipsychotics during 1year. At baseline, 498 patients have been included. The first (baseline) and the last assessment (12months after baseline) were used for the analyses. Predictors of quality of life were determined using regression analyses. We tested the complex longitudinal interrelations between baseline and outcome measures with structural equation models. Unmet needs were not definitively confirmed as a predictor of subsequent quality of life, unless unmet needs changing to no needs were separated from unmet needs changing to met needs. Each unmet need that changed to no need enhanced the quality of life (mean score 1-7) by 0.136 scale points. This study suggests that when studying quality of life and needs for treatment, it is crucial to differentiate whether unmet needs disappeared or whether they were met, as the former has a stronger impact on quality of lif

    Unmet needs in patients with first-episode schizophrenia: a longitudinal perspective

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    Background This study aimed to identify the course of unmet needs by patients with a first episode of schizophrenia and to determine associated variables. Method We investigated baseline assessments in the European First Episode Schizophrenia Trial (EUFEST) and also follow-up interviews at 6 and 12 months. Latent class growth analysis was used to identify patient groups based on individual differences in the development of unmet needs. Multinomial logistic regression determined the predictors of group membership. Results Four classes were identified. Three differed in their baseline levels of unmet needs whereas the fourth had a marked decrease in such needs. Main predictors of class membership were prognosis and depression at baseline, and the quality of life and psychosocial intervention at follow-up. Depression at follow-up did not vary among classes. Conclusions We identified subtypes of patients with different courses of unmet needs. Prognosis of clinical improvement was a better predictor for the decline in unmet needs than was psychopathology. Needs concerning social relationships were particularly persistent in patients who remained high in their unmet needs and who lacked additional psychosocial treatmen

    Evidence for the role of EPHX2 gene variants in anorexia nervosa.

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    Anorexia nervosa (AN) and related eating disorders are complex, multifactorial neuropsychiatric conditions with likely rare and common genetic and environmental determinants. To identify genetic variants associated with AN, we pursued a series of sequencing and genotyping studies focusing on the coding regions and upstream sequence of 152 candidate genes in a total of 1205 AN cases and 1948 controls. We identified individual variant associations in the Estrogen Receptor-ß (ESR2) gene, as well as a set of rare and common variants in the Epoxide Hydrolase 2 (EPHX2) gene, in an initial sequencing study of 261 early-onset severe AN cases and 73 controls (P=0.0004). The association of EPHX2 variants was further delineated in: (1) a pooling-based replication study involving an additional 500 AN patients and 500 controls (replication set P=0.00000016); (2) single-locus studies in a cohort of 386 previously genotyped broadly defined AN cases and 295 female population controls from the Bogalusa Heart Study (BHS) and a cohort of 58 individuals with self-reported eating disturbances and 851 controls (combined smallest single locus P<0.01). As EPHX2 is known to influence cholesterol metabolism, and AN is often associated with elevated cholesterol levels, we also investigated the association of EPHX2 variants and longitudinal body mass index (BMI) and cholesterol in BHS female and male subjects (N=229) and found evidence for a modifying effect of a subset of variants on the relationship between cholesterol and BMI (P<0.01). These findings suggest a novel association of gene variants within EPHX2 to susceptibility to AN and provide a foundation for future study of this important yet poorly understood condition

    Correlation Analysis of Genetic Admixture and Social Identification with Body Mass Index in a Native American Community

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    OBJECTIVES: Body mass index (BMI) is a well-known measure of obesity with a multitude of genetic and non-genetic determinants. Identifying the underlying factors associated with BMI is difficult because of its multifactorial etiology that varies as a function of geoethnic background and socioeconomic setting. Thus, we pursued a study exploring the influence of the degree of Native American admixture on BMI (as well as weight and height individually) in a community sample of Native Americans (n = 846) while accommodating a variety of socioeconomic and cultural factors. METHODS: Participants' degree of Native American (NA) ancestry was estimated using a genome-wide panel of markers. The participants also completed an extensive survey of cultural and social identity measures: the Indian Culture Scale (ICS) and the Orthogonal Cultural Identification Scale (OCIS). Multiple linear regression was used to examine the relation between these measures and BMI. RESULTS: Our results suggest that BMI is correlated positively with the proportion of NA ancestry. Age was also significantly associated with BMI, while gender and socioeconomic measures (education and income) were not. For the two cultural identity measures, the ICS showed a positive correlation with BMI, while OCIS was not associated with BMI. CONCLUSIONS: Taken together, these results suggest that genetic and cultural environmental factors, rather than socioeconomic factors, account for a substantial proportion of variation in BMI in this population. Further, significant correlations between degree of NA ancestry and BMI suggest that admixture mapping may be appropriate to identify loci associated with BMI in this population
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