26 research outputs found

    Statistical distribution models : goodness of fit tests

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    The purpose of a one-sample test of fit is to give an objective measure of how well a probability model agrees with observed data. Here we discuss the test of Karl Pearson and derivatives of it, tests based on the empirical distribution function and the construction of the Neyman-Barton smooth tests. In the final section, we then address some modern developments in smooth testing: diagnostics, Cholesky components, data-driven tests and model selection. Other tests of fit, such as correlation tests and Laplace transform tests, are not considered here

    Early Gnathostome Phylogeny Revisited: Multiple Method Consensus

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    This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.A series of recent studies recovered consistent phylogenetic scenarios of jawed vertebrates, such as the paraphyly of placoderms with respect to crown gnathostomes, and antiarchs as the sister group of all other jawed vertebrates. However, some of the hylogenetic relationships within the group have remained controversial, such as the positions of Entelognathus, ptyctodontids, and the Guiyu-lineage that comprises Guiyu, Psarolepis and Achoania. The revision of the dataset in a recent study reveals a modified phylogenetic hypothesis, which shows that some of these phylogenetic conflicts were sourced from a few inadvertent miscodings. The interrelationships of early gnathostomes are addressed based on a combined new dataset with 103 taxa and 335 characters, which is the most comprehensive morphological dataset constructed to date. This dataset is investigated in a phylogenetic context using maximum parsimony (MP), Bayesian inference (BI) and maximum likelihood (ML) approaches in an attempt to explore the consensus and incongruence between the hypotheses of early gnathostome interrelationships recovered from different methods. Our findings consistently corroborate the paraphyly of placoderms, all `acanthodians' as a paraphyletic stem group of chondrichthyans, Entelognathus as a stem gnathostome, and the Guiyu-lineage as stem sarcopterygians. The incongruence using different methods is less significant than the consensus, and mainly relates to the positions of the placoderm Wuttagoonaspis, the stem chondrichthyan Ramirosuarezia, and the stem osteichthyan LophosteusÐthe taxa that are either poorly known or highly specialized in character complement. Given that the different performances of each phylogenetic approach, our study provides an empirical case that the multiple phylogenetic analyses of morphological data are mutually complementary rather than redundant

    Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci.

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    We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease

    State of the Climate in 2016

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    Comparing nonparametric tests of equality of means for randomized block designs

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    A number of nonparametric tests are compared empirically for a randomized block layout. We assess tests appropriate for when the data are not consistent with normality or when outliers invalidate traditional analysis of variance (ANOVA) tests. The objective is to assess, within this setting, tests that use ranks within blocks, the rank transform procedure that ranks the complete sample and continuous analogs of the Cochran-Mantel-Haenszel tests. The usual linear model is assumed, and our primary foci are tests of equality of means and component tests that assess linear and quadratic trends in the means. These tests include the traditional Page and Friedman tests. We conclude that the rank transform tests have competitive power and warrant greater use than is currently apparent

    Sensitivity of inverse estimation of annual mean CO2_2 sources and sinks to ocean-only sites versus all-sites observational networks

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    International audienceInverse estimation of carbon dioxide (CO2_2) sources and sinks uses atmospheric CO2_2 observations, mostly made near the Earth's surface. However, transport models used in such studies lack perfect representation of atmospheric dynamics and thus often fail to produce unbiased forward simulations. The error is generally larger for observations over the land than those over the remote/marine locations. The range of this error is estimated by using multiple transport models (16 are used here). We have estimated the remaining differences in CO2_2 fluxes due to the use of ocean-only versus all-sites (i.e., over ocean and land) observations of CO2_2 in a time-independent inverse modeling framework. The fluxes estimated using the ocean-only networks are more robust compared to those obtained using all-sites networks. This makes the global, hemispheric, and regional flux determination less dependent on the selection of transport model and observation network

    The genetic architecture of type 2 diabetes.

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    The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of the heritability of this disease. Here, to test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole-genome sequencing in 2,657 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes
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