scholarly journals Online Bayesian Phylodynamic Inference in BEAST with Application to Epidemic Reconstruction

2020 ◽  
Vol 37 (6) ◽  
pp. 1832-1842 ◽  
Author(s):  
Mandev S Gill ◽  
Philippe Lemey ◽  
Marc A Suchard ◽  
Andrew Rambaut ◽  
Guy Baele

Abstract Reconstructing pathogen dynamics from genetic data as they become available during an outbreak or epidemic represents an important statistical scenario in which observations arrive sequentially in time and one is interested in performing inference in an “online” fashion. Widely used Bayesian phylogenetic inference packages are not set up for this purpose, generally requiring one to recompute trees and evolutionary model parameters de novo when new data arrive. To accommodate increasing data flow in a Bayesian phylogenetic framework, we introduce a methodology to efficiently update the posterior distribution with newly available genetic data. Our procedure is implemented in the BEAST 1.10 software package, and relies on a distance-based measure to insert new taxa into the current estimate of the phylogeny and imputes plausible values for new model parameters to accommodate growing dimensionality. This augmentation creates informed starting values and re-uses optimally tuned transition kernels for posterior exploration of growing data sets, reducing the time necessary to converge to target posterior distributions. We apply our framework to data from the recent West African Ebola virus epidemic and demonstrate a considerable reduction in time required to obtain posterior estimates at different time points of the outbreak. Beyond epidemic monitoring, this framework easily finds other applications within the phylogenetics community, where changes in the data—in terms of alignment changes, sequence addition or removal—present common scenarios that can benefit from online inference.

2016 ◽  
Author(s):  
Kassian Kobert ◽  
Alexandros Stamatakis ◽  
Tomáš Flouri

The phylogenetic likelihood function is the major computational bottleneck in several applications of evolutionary biology such as phylogenetic inference, species delimitation, model selection and divergence times estimation. Given the alignment, a tree and the evolutionary model parameters, the likelihood function computes the conditional likelihood vectors for every node of the tree. Vector entries for which all input data are identical result in redundant likelihood operations which, in turn, yield identical conditional values. Such operations can be omitted for improving run-time and, using appropriate data structures, reducing memory usage. We present a fast, novel method for identifying and omitting such redundant operations in phylogenetic likelihood calculations, and assess the performance improvement and memory saving attained by our method. Using empirical and simulated data sets, we show that a prototype implementation of our method yields up to 10-fold speedups and uses up to 78% less memory than one of the fastest and most highly tuned implementations of the phylogenetic likelihood function currently available. Our method is generic and can seamlessly be integrated into any phylogenetic likelihood implementation.


2003 ◽  
Vol 42 (05) ◽  
pp. 215-219
Author(s):  
G. Platsch ◽  
A. Schwarz ◽  
K. Schmiedehausen ◽  
B. Tomandl ◽  
W. Huk ◽  
...  

Summary: Aim: Although the fusion of images from different modalities may improve diagnostic accuracy, it is rarely used in clinical routine work due to logistic problems. Therefore we evaluated performance and time needed for fusing MRI and SPECT images using a semiautomated dedicated software. Patients, material and Method: In 32 patients regional cerebral blood flow was measured using 99mTc ethylcystein dimer (ECD) and the three-headed SPECT camera MultiSPECT 3. MRI scans of the brain were performed using either a 0,2 T Open or a 1,5 T Sonata. Twelve of the MRI data sets were acquired using a 3D-T1w MPRAGE sequence, 20 with a 2D acquisition technique and different echo sequences. Image fusion was performed on a Syngo workstation using an entropy minimizing algorithm by an experienced user of the software. The fusion results were classified. We measured the time needed for the automated fusion procedure and in case of need that for manual realignment after automated, but insufficient fusion. Results: The mean time of the automated fusion procedure was 123 s. It was for the 2D significantly shorter than for the 3D MRI datasets. For four of the 2D data sets and two of the 3D data sets an optimal fit was reached using the automated approach. The remaining 26 data sets required manual correction. The sum of the time required for automated fusion and that needed for manual correction averaged 320 s (50-886 s). Conclusion: The fusion of 3D MRI data sets lasted significantly longer than that of the 2D MRI data. The automated fusion tool delivered in 20% an optimal fit, in 80% manual correction was necessary. Nevertheless, each of the 32 SPECT data sets could be merged in less than 15 min with the corresponding MRI data, which seems acceptable for clinical routine use.


2019 ◽  
Vol 8 (8) ◽  
pp. 72-85
Author(s):  
Nilanjana Ghoshal ◽  
Mst Tania Parveen ◽  
Dr Asraful Alam

In India, traditionally and from time immemorial, marriage has always been a sacred bond for people of this country. The aim of this study is to explain a socially sanctioned sex relationship involving people of two opposite gender whose relationship is expected to endure beyond time required for gestation. The functional method of the study has been set up on the field-based observation to find out the reasons behind rising of marital disharmony among working couples. But the problem is initially in modern times the concept of marriage is gradually taking a different turn between couples. Hence the focus of this paper is to study the various factors giving rise to marital disharmonies among working couples in urban India and how these discords can be solved so that couples can lead a happy harmonious married life ahead. Survey has been done in the city of Kolkata taking people from various walks of life. As Kolkata is one of the major Metropolitan cities of India it was easier to find people belonging to different professions. The result of this study is every marriage brings challenges in life. Maximum working couples are losing attachment with each other as they have lack of time for each other. Bringing work at home, sharing of parenthood, indifference towards each other, lack of adjustments are the causes for which level of disharmony is increasing.


Mathematics ◽  
2021 ◽  
Vol 9 (16) ◽  
pp. 1850
Author(s):  
Rashad A. R. Bantan ◽  
Farrukh Jamal ◽  
Christophe Chesneau ◽  
Mohammed Elgarhy

Unit distributions are commonly used in probability and statistics to describe useful quantities with values between 0 and 1, such as proportions, probabilities, and percentages. Some unit distributions are defined in a natural analytical manner, and the others are derived through the transformation of an existing distribution defined in a greater domain. In this article, we introduce the unit gamma/Gompertz distribution, founded on the inverse-exponential scheme and the gamma/Gompertz distribution. The gamma/Gompertz distribution is known to be a very flexible three-parameter lifetime distribution, and we aim to transpose this flexibility to the unit interval. First, we check this aspect with the analytical behavior of the primary functions. It is shown that the probability density function can be increasing, decreasing, “increasing-decreasing” and “decreasing-increasing”, with pliant asymmetric properties. On the other hand, the hazard rate function has monotonically increasing, decreasing, or constant shapes. We complete the theoretical part with some propositions on stochastic ordering, moments, quantiles, and the reliability coefficient. Practically, to estimate the model parameters from unit data, the maximum likelihood method is used. We present some simulation results to evaluate this method. Two applications using real data sets, one on trade shares and the other on flood levels, demonstrate the importance of the new model when compared to other unit models.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Amara Khan ◽  
Andrea Markus ◽  
Thomas Rittmann ◽  
Jonas Albers ◽  
Frauke Alves ◽  
...  

AbstractX-ray based lung function (XLF) as a planar method uses dramatically less X-ray dose than computed tomography (CT) but so far lacked the ability to relate its parameters to pulmonary air volume. The purpose of this study was to calibrate the functional constituents of XLF that are biomedically decipherable and directly comparable to that of micro-CT and whole-body plethysmography (WBP). Here, we developed a unique set-up for simultaneous assessment of lung function and volume using XLF, micro-CT and WBP on healthy mice. Our results reveal a strong correlation of lung volumes obtained from radiographic XLF and micro-CT and demonstrate that XLF is superior to WBP in sensitivity and precision to assess lung volumes. Importantly, XLF measurement uses only a fraction of the radiation dose and acquisition time required for CT. Therefore, the redefined XLF approach is a promising tool for preclinical longitudinal studies with a substantial potential of clinical translation.


Author(s):  
Yi Zhang ◽  
Tao Wang ◽  
Yan Wang ◽  
Kun Xia ◽  
Jinchen Li ◽  
...  

AbstractNeurodevelopmental disorders (NDDs) are a group of diseases characterized by high heterogeneity and frequently co-occurring symptoms. The mutational spectrum in patients with NDDs is largely incomplete. Here, we sequenced 547 genes from 1102 patients with NDDs and validated 1271 potential functional variants, including 108 de novo variants (DNVs) in 78 autosomal genes and seven inherited hemizygous variants in six X chromosomal genes. Notably, 36 of these 78 genes are the first to be reported in Chinese patients with NDDs. By integrating our genetic data with public data, we prioritized 212 NDD candidate genes with FDR < 0.1, including 17 novel genes. The novel candidate genes interacted or were co-expressed with known candidate genes, forming a functional network involved in known pathways. We highlighted MSL2, which carried two de novo protein-truncating variants (p.L192Vfs*3 and p.S486Ifs*11) and was frequently connected with known candidate genes. This study provides the mutational spectrum of NDDs in China and prioritizes 212 NDD candidate genes for further functional validation and genetic counseling.


Author(s):  
Thomas Blaschke ◽  
Jürgen Bajorath

AbstractExploring the origin of multi-target activity of small molecules and designing new multi-target compounds are highly topical issues in pharmaceutical research. We have investigated the ability of a generative neural network to create multi-target compounds. Data sets of experimentally confirmed multi-target, single-target, and consistently inactive compounds were extracted from public screening data considering positive and negative assay results. These data sets were used to fine-tune the REINVENT generative model via transfer learning to systematically recognize multi-target compounds, distinguish them from single-target or inactive compounds, and construct new multi-target compounds. During fine-tuning, the model showed a clear tendency to increasingly generate multi-target compounds and structural analogs. Our findings indicate that generative models can be adopted for de novo multi-target compound design.


2020 ◽  
Vol 70 (1) ◽  
pp. 145-161 ◽  
Author(s):  
Marnus Stoltz ◽  
Boris Baeumer ◽  
Remco Bouckaert ◽  
Colin Fox ◽  
Gordon Hiscott ◽  
...  

Abstract We describe a new and computationally efficient Bayesian methodology for inferring species trees and demographics from unlinked binary markers. Likelihood calculations are carried out using diffusion models of allele frequency dynamics combined with novel numerical algorithms. The diffusion approach allows for analysis of data sets containing hundreds or thousands of individuals. The method, which we call Snapper, has been implemented as part of the BEAST2 package. We conducted simulation experiments to assess numerical error, computational requirements, and accuracy recovering known model parameters. A reanalysis of soybean SNP data demonstrates that the models implemented in Snapp and Snapper can be difficult to distinguish in practice, a characteristic which we tested with further simulations. We demonstrate the scale of analysis possible using a SNP data set sampled from 399 fresh water turtles in 41 populations. [Bayesian inference; diffusion models; multi-species coalescent; SNP data; species trees; spectral methods.]


1984 ◽  
Vol 106 (1) ◽  
pp. 29-35 ◽  
Author(s):  
P. Cawley

The susceptibility to bias error of two methods for computing transfer (frequency response) functions from spectra produced by FFT-based analyzers using random excitation has been investigated. Results from tests with an FFT analyzer on a single degree-of-freedom system set up on an analogue computer show good agreement with the theoretical predictions. It has been shown that, around resonance, the bias error in the transfer function estimate H2 (Syy/Sxy*) is considerably less than that in the more commonly used estimate, H1 (Sxy/Sxx). The record length, and hence the testing time, required for a given accuracy is reduced by over 50 percent if the H2 calculation procedure is used. The analysis has also shown that if shaker excitation is used on lightly damped structures with low modal mass, it is important to minimize the mass of the force gage and the moving element of the shaker.


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