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https://www.readbyqxmd.com/read/28334312/efficient-inference-for-genetic-association-studies-with-multiple-outcomes
#1
Helene Ruffieux, Anthony C Davison, Jorg Hager, Irina Irincheeva
Combined inference for heterogeneous high-dimensional data is critical in modern biology, where clinical and various kinds of molecular data may be available from a single study. Classical genetic association studies regress a single clinical outcome on many genetic variants one by one, but there is an increasing demand for joint analysis of many molecular outcomes and genetic variants in order to unravel functional interactions. Unfortunately, most existing approaches to joint modeling are either too simplistic to be powerful or are impracticable for computational reasons...
March 16, 2017: Biostatistics
https://www.readbyqxmd.com/read/28334223/is-bamm-flawed-theoretical-and-practical-concerns-in-the-analysis-of-multi-rate-diversification-models
#2
Daniel L Rabosky, Jonathan S Mitchell, Jonathan Chang
BAMM (Bayesian Analysis of Macroevolutionary Mixtures) is a statistical framework that uses reversible jump MCMC to infer complex macroevolutionary dynamics of diversification and phenotypic evolution on phylogenetic trees. A recent article by Moore and coauthors (MEA) reported a number of theoretical and practical concerns with BAMM. Major claims from MEA are that (1) BAMM's likelihood function is incorrect, because it does not account for unobserved rate shifts; (2) the posterior distribution on the number of rate shifts is overly sensitive to the prior; and (3) diversification rate estimates from BAMM are unreliable...
February 21, 2017: Systematic Biology
https://www.readbyqxmd.com/read/28333230/bayesian-analysis-of-evolutionary-divergence-with-genomic-data-under-diverse-demographic-models
#3
Yujin Chung, Jody Hey
We present a new Bayesian method for estimating demographic and phylogenetic history using population genomic data. Several key innovations are introduced that allow the study of diverse models within an Isolation with Migration framework. The new method implements a 2-step analysis, with an initial Markov chain Monte Carlo (MCMC) phase that samples simple coalescent trees, followed by the calculation of the joint posterior density for the parameters of a demographic model. In step 1, the MCMC sampling phase, the method uses a reduced state space, consisting of coalescent trees without migration paths, and a simple importance sampling distribution without the demography of interest...
February 25, 2017: Molecular Biology and Evolution
https://www.readbyqxmd.com/read/28321898/a-generalized-mixture-model-applied-to-diabetes-incidence-data
#4
Daiane Aparecida Zuanetti, Luis Aparecido Milan
We present a generalization of the usual (independent) mixture model to accommodate a Markovian first-order mixing distribution. We propose the data-driven reversible jump, a Markov chain Monte Carlo (MCMC) procedure, for estimating the a posteriori probability for each model in a model selection procedure and estimating the corresponding parameters. Simulated datasets show excellent performance of the proposed method in the convergence, model selection, and precision of parameters estimates. Finally, we apply the proposed method to analyze USA diabetes incidence datasets...
March 21, 2017: Biometrical Journal. Biometrische Zeitschrift
https://www.readbyqxmd.com/read/28301529/applying-diffusion-based-markov-chain-monte-carlo
#5
Radu Herbei, Rajib Paul, L Mark Berliner
We examine the performance of a strategy for Markov chain Monte Carlo (MCMC) developed by simulating a discrete approximation to a stochastic differential equation (SDE). We refer to the approach as diffusion MCMC. A variety of motivations for the approach are reviewed in the context of Bayesian analysis. In particular, implementation of diffusion MCMC is very simple to set-up, even in the presence of nonlinear models and non-conjugate priors. Also, it requires comparatively little problem-specific tuning. We implement the algorithm and assess its performance for both a test case and a glaciological application...
2017: PloS One
https://www.readbyqxmd.com/read/28290281/bioinactivation-software-for-modelling-dynamic-microbial-inactivation
#6
Alberto Garre, Pablo S Fernández, Roland Lindqvist, Jose A Egea
This contribution presents the bioinactivation software, which implements functions for the modelling of isothermal and non-isothermal microbial inactivation. This software offers features such as user-friendliness, modelling of dynamic conditions, possibility to choose the fitting algorithm and generation of prediction intervals. The software is offered in two different formats: Bioinactivation core and Bioinactivation SE. Bioinactivation core is a package for the R programming language, which includes features for the generation of predictions and for the fitting of models to inactivation experiments using non-linear regression or a Markov Chain Monte Carlo algorithm (MCMC)...
March 2017: Food Research International
https://www.readbyqxmd.com/read/28284835/randomized-trial-of-a-peer-led-telephone-based-empowerment-intervention-for-persons-with-chronic-spinal-cord-injury-improves-health-self-management
#7
Bethlyn Vergo Houlihan, Miriam Brody, Sarah Everhart-Skeels, Diana Pernigotti, Sam Burnett, Judi Zazula, Christa Green, Stathis Hasiotis, Timothy Belliveau, Subramani Seetharama, David Rosenblum, Alan Jette
OBJECTIVE: To evaluate the impact of "My Care My Call" (MCMC), a peer-led, telephone-based health self-management intervention in adults with chronic spinal cord injury (SCI). DESIGN: Single-blinded randomized controlled trial SETTING: General community PARTICIPANTS: Convenience sample of 84 adults with SCI (X= 9.9 years post-SCI); X=46 years old; 73.8% male; 44% with paraplegia; and 58% White. INTERVENTIONS: Trained Peer Health Coaches (PHC) applied the person-centered health self-management intervention with 42 experimental subjects over 6 months on a tapered call schedule...
March 8, 2017: Archives of Physical Medicine and Rehabilitation
https://www.readbyqxmd.com/read/28273358/estimating-thermal-performance-curves-from-repeated-field-observations
#8
Evan S Childress, Benjamin H Letcher
Estimating thermal performance of organisms is critical for understanding population distributions and dynamics and predicting responses to climate change. Typically, performance curves are estimated using laboratory studies to isolate temperature effects, but other abiotic and biotic factors influence temperature-performance relationships in nature reducing these models' predictive ability. We present a model for estimating thermal performance curves from repeated field observations that includes environmental and individual variation...
March 8, 2017: Ecology
https://www.readbyqxmd.com/read/28268605/parameter-estimation-for-gene-regulatory-networks-a-two-stage-mcmc-bayesian-approach
#9
Niannan Xue, Wei Pan, Yike Guo
Genetic regulatory networks have emerged as a useful way to elucidate the biochemical pathways for biological functions. Yet, determination of the exact parametric forms for these models remain a major challenge. In this paper, we present a novel computational approach implemented in C++ to solve this inverse problem. This takes the form of an optimization stage first after which Bayesian filtering takes place. The key advantage of such a flexible, general and robust approach is that it provides us with a joint probability distribution of the model parameters instead of single estimates, which we can propagate to final predictions...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28263987/inferring-epidemiological-parameters-from-phylogenies-using-regression-abc-a-comparative-study
#10
Emma Saulnier, Olivier Gascuel, Samuel Alizon
Inferring epidemiological parameters such as the R0 from time-scaled phylogenies is a timely challenge. Most current approaches rely on likelihood functions, which raise specific issues that range from computing these functions to finding their maxima numerically. Here, we present a new regression-based Approximate Bayesian Computation (ABC) approach, which we base on a large variety of summary statistics intended to capture the information contained in the phylogeny and its corresponding lineage-through-time plot...
March 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28239392/zoeppritz-based-avo-inversion-using-an-improved-markov-chain-monte-carlo-method
#11
Xin-Peng Pan, Guang-Zhi Zhang, Jia-Jia Zhang, Xing-Yao Yin
The conventional Markov chain Monte Carlo (MCMC) method is limited to the selected shape and size of proposal distribution and is not easy to start when the initial proposal distribution is far away from the target distribution. To overcome these drawbacks of the conventional MCMC method, two useful improvements in MCMC method, adaptive Metropolis (AM) algorithm and delayed rejection (DR) algorithm, are attempted to be combined. The AM algorithm aims at adapting the proposal distribution by using the generated estimators, and the DR algorithm aims at enhancing the efficiency of the improved MCMC method...
2017: Pet Sci
https://www.readbyqxmd.com/read/28226784/parameter-estimation-for-gene-regulatory-networks-a-two-stage-mcmc-bayesian-approach
#12
Niannan Xue, Wei Pan, Yike Guo, Niannan Xue, Wei Pan, Yike Guo, Wei Pan, Yike Guo, Niannan Xue
Genetic regulatory networks have emerged as a useful way to elucidate the biochemical pathways for biological functions. Yet, determination of the exact parametric forms for these models remain a major challenge. In this paper, we present a novel computational approach implemented in C++ to solve this inverse problem. This takes the form of an optimization stage first after which Bayesian filtering takes place. The key advantage of such a flexible, general and robust approach is that it provides us with a joint probability distribution of the model parameters instead of single estimates, which we can propagate to final predictions...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28216881/specific-pcr-identification-between-peucedanum-praeruptorum-and-angelica-decursiva-and-identification-between-them-and-adulterant-using-dna-barcode
#13
Bang-Xing Han, Yuan Yuan, Lu-Qi Huang, Qun Zhao, Ling-Ling Tan, Xiang-Wen Song, Xiao-Mei He, Tao Xu, Feng Liu, Jian Wang
BACKGROUND: The traditional Chinese medicine (TCM) Qianhu and Zihuaqianhu are the dried roots of Peucedanum praeruptorum and Angelica decursiva, respectively. Since the plant sources of Qianhu and Zihuaqianhu are more complex, the chemical compositions of P. praeruptorum and A. decursiva are significantly different, and many adulterants exist because of the differences in traditional understanding and medication habits. Therefore, the rapid and accurate identification methods are required...
January 2017: Pharmacognosy Magazine
https://www.readbyqxmd.com/read/28200071/adaptive-mcmc-in-bayesian-phylogenetics-an-application-to-analyzing-partitioned-data-in-beast
#14
Guy Baele, Philippe Lemey, Andrew Rambaut, Marc A Suchard
No abstract text is available yet for this article.
February 13, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28193551/a-gibbs-sampling-method-to-determine-biomarkers-for-asthma
#15
Zhi-Jian Huang, Qin-Hai Shen, Yan-Sheng Wu, Ya-Li Huang
PURPOSE: To identify potential biomarkers and to uncover the mechanisms underlying asthma based on Gibbs sampling. METHODS: The molecular functions (MFs) with genes greater than 5 were determined using AnnotationMFGO of BAGS package, and the obtained MFs were then transformed to Markov chain (MC). Gibbs sampling was conducted to obtain a new MC. Meanwhile, the average probabilities of MFs were computed via MC Monte Carlo (MCMC) algorithm, followed by identification of differentially expressed MFs based on the probabilities of MF more than 0...
January 22, 2017: Computational Biology and Chemistry
https://www.readbyqxmd.com/read/28187712/vmcmc-a-graphical-and-statistical-analysis-tool-for-markov-chain-monte-carlo-traces
#16
Raja H Ali, Mikael Bark, Jorge Miró, Sayyed A Muhammad, Joel Sjöstrand, Syed M Zubair, Raja M Abbas, Lars Arvestad
BACKGROUND: MCMC-based methods are important for Bayesian inference of phylogeny and related parameters. Although being computationally expensive, MCMC yields estimates of posterior distributions that are useful for estimating parameter values and are easy to use in subsequent analysis. There are, however, sometimes practical difficulties with MCMC, relating to convergence assessment and determining burn-in, especially in large-scale analyses. Currently, multiple software are required to perform, e...
February 10, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28185583/probabilistic-inference-of-lateral-gene-transfer-events
#17
Mehmood Alam Khan, Owais Mahmudi, Ikram Ullah, Lars Arvestad, Jens Lagergren
BACKGROUND: Lateral gene transfer (LGT) is an evolutionary process that has an important role in biology. It challenges the traditional binary tree-like evolution of species and is attracting increasing attention of the molecular biologists due to its involvement in antibiotic resistance. A number of attempts have been made to model LGT in the presence of gene duplication and loss, but reliably placing LGT events in the species tree has remained a challenge. RESULTS: In this paper, we propose probabilistic methods that samples reconciliations of the gene tree with a dated species tree and computes maximum a posteriori probabilities...
November 11, 2016: BMC Bioinformatics
https://www.readbyqxmd.com/read/28182726/spatial-patterns-of-multidrug-resistant-tuberculosis-and-relationships-to-socio-economic-demographic-and-household-factors-in-northwest-ethiopia
#18
Kefyalew Addis Alene, Kerri Viney, Emma S McBryde, Archie C A Clements
BACKGROUND: Understanding the geographical distribution of multidrug-resistant tuberculosis (MDR-TB) in high TB burden countries such as Ethiopia is crucial for effective control of TB epidemics in these countries, and thus globally. We present the first spatial analysis of multidrug resistant tuberculosis, and its relationship to socio-economic, demographic and household factors in northwest Ethiopia. METHODS: An ecological study was conducted using data on patients diagnosed with MDR-TB at the University of Gondar Hospital MDR-TB treatment centre, for the period 2010 to 2015...
2017: PloS One
https://www.readbyqxmd.com/read/28170425/phylogeny-and-biogeography-of-the-amphi-pacific-genus-aphananthe
#19
Mei-Qing Yang, De-Zhu Li, Jun Wen, Ting-Shuang Yi
Aphananthe is a small genus of five species showing an intriguing amphi-Pacific distribution in eastern, southern and southeastern Asia, Australia, and Mexico, also with one species in Madagascar. The phylogenetic relationships of Aphananthe were reconstructed with two nuclear (ITS & ETS) and two plastid (psbA-trnH & trnL-trnF) regions. Clade divergence times were estimated with a Bayesian approach, and the ancestral areas were inferred using the dispersal-extinction-cladogenesis and Bayesian Binary MCMC analyses...
2017: PloS One
https://www.readbyqxmd.com/read/28166715/bmodeltest-bayesian-phylogenetic-site-model-averaging-and-model-comparison
#20
Remco R Bouckaert, Alexei J Drummond
BACKGROUND: Reconstructing phylogenies through Bayesian methods has many benefits, which include providing a mathematically sound framework, providing realistic estimates of uncertainty and being able to incorporate different sources of information based on formal principles. Bayesian phylogenetic analyses are popular for interpreting nucleotide sequence data, however for such studies one needs to specify a site model and associated substitution model. Often, the parameters of the site model is of no interest and an ad-hoc or additional likelihood based analysis is used to select a single site model...
February 6, 2017: BMC Evolutionary Biology
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