Find research datasets worth reusing

opencc-by-4.0Feb 2022View details →

Bayesian machine learning analysis of single-molecule fluorescence colocalization images

Data files for the "Bayesian machine learning analysis of single-molecule fluorescence colocalization images" manuscript.

opencc-by-4.0Jul 2024View details →

Bayesian analysis of (3+1)D relativistic nuclear dynamics with the RHIC beam energy scan data

This dataset contains the MCMC chain (LHD+HPP) without any constraints on the parameters for the (3+1)D Bayesian inference study for the RHIC beam energy scan program. We also provide the nine trained emulator objects, which were generated with the code available at <a title="GPBayesTools-HIC: v1.1.0" href="https://doi.org/10.5281/zenodo.12807892" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.12807892</a>. The training data is given in pickle format as dictionaries for the training points. The first 1000 points in the files correspond to the Latin Hypercube design points and the last 100 points are points sampled from the posterior distribution.

opencc-by-4.0Jun 2019View details →

Code + simulated + publically accessable data for "Evaluating health facility access using Bayesian spatial models and location analysis methods"

# README These files contain r data objects and R files that represent the key details of the paper, "Evaluating health facility access using Bayesian spatial models and location analysis methods". The following datasources are available for simulation of some of the ideas in the paper. - dat_grid_sim: simulated data of the grid and grid cells - dat_ohca_cv_sim: simulated data containing the cross validated test/training sets of OHCA data - dat_ohca_sim: simulated OHCA event data - dat_aed_sim: simulated AED location data - dat_bldg_sim: simulated building location data - dat_municipality_sim: simulated municipality information - table_1: Table 1 information containing key demographic data These data were produced using the code in 01-create-sim-data.R, and one of the statistical models is demonstrated in 02-demo-inla-model.R In terms of the paper itself, the functions and code used in the manuscript are located in: * 01_tidy.Rmd - analysis code used to tidy up the data * 02_fit_fixed_all_cv.Rmd - analysis code used to place AEDs * 02_model.Rmd - analysis code used to fit the model in INLA * 03_manuscript.Rmd - Full code and text used to create the paper * 04_supp_materials.Rmd - full code and text used to create the supplementary materials The following files are a part of an R package "swatial" that was developed along with the paper. These files are: * DESCRIPTION * NAMESPACE * LICENSE * LICENSE.md * decay.R * spherical-distance.R * test-figure-data-matches.R * test-table-data-matches.R * testthat.R * tidy-inla.R * tidy-posterior-coefs.R * tidy-predictions.R * utils-pipe.R * All files that end in .Rd are documentation files for the functions. ## Regarding data sources Census information for Ticino was transcribed from the Annual Statistical Report of Canton Ticino from years 2010 to 2015. This data was taken from their publicly accessible annual reports - for example: (https://www3.ti.ch/DFE/DR/USTAT/allegati/volume/ast_2015.pdf). The raw data was extracted from these annual reports, and placed into the file: "swiss_census_popn_2010_2015.xlsx". These data are put into analysis ready format in the file “01_tidy.Rmd” Housing and other relevant geospatial data can be accessed via http://map.housing-stat.ch/ and https://data.geo.admin.ch/. The maps of buildings from the REA (Register of Buildings and Dwellings) can be found here: https://map.geo.admin.ch/?zoom=11&bgLayer=ch.swisstopo.pixelkarte-grau&lang=en&topic=ech&layers=ch.bfs.gebaeude_wohnungs_register,ch.swisstopo.swissboundaries3d-gemeinde-flaeche.fill,ch.bfs.volkszaehlung-gebaeudestatistik_gebaeude,ch.bfs.volkszaehlung-gebaeudestatistik_wohnungen,ch.swisstopo.swissbuildings3d_1.metadata,ch.swisstopo.swissbuildings3d_2.metadata&E=2717616.28&N=1096597.25&catalogNodes=687,696&layers_timestamp=,,2016,2016,,&layers_visibility=true,false,false,false,false,false&layers_opacity=1,1,1,1,1,0.75 For further enquiries on this data, contact the Swiss federal Office of Statistics at the details listed here: https://www.bfs.admin.ch/bfs/en/home/services/contact.html The shapefiles of the Comuni can be accessed here: https://www4.ti.ch/dfe/de/ucr/documentazione/download-file/?noMobile=1 Data from the people living in the Municipalities in Ticino can be downloaded here: https://www3.ti.ch/DFE/DR/USTAT/index.php?fuseaction=dati.home&tema=33&id2=61&id3=65&c1=01&c2=02&c3=02 ## Future work In the future, these functions from the paper may be generalised and put into their own package. If that happens, this repository will be updated with a link to updated functions.

opencc-by-4.0Sep 2024View details →

Bayesian Analysis of Paleotsunami Sources: Data and Stochastic Simulations

This repository contains the datasets utilized in the research titled “Tracing the Sources of Paleotsunamis Using Bayesian Frameworks.” Each dataset is integral to the analysis and reconstruction efforts undertaken in the study.   File Descriptions   1. CorrectedShoreline_jogan_deposit_data.csv   This file contains paleotsunami data collected by Sugawara et al. The data has been corrected to account for the shoreline position at the time of the paleotsunami event.   Reference: Sugawara, D., Goto, K., Imamura, F., Matsumoto, H., & Minoura, K. (2012). Assessing the magnitude of the 869 Jogan tsunami using sedimentary deposits: Prediction and consequence of the 2011 Tohoku-oki tsunami. Sedimentary Geology, 282, 14–26.   2. Stochastic_samples.zip   This archive contains the stochastic samples generated for the Japan Trench, utilizing the coupling distribution model from Loveless et al.   Reference: Loveless, J. P., & Meade, B. J. (2011). Spatial correlation of interseismic coupling and coseismic rupture extent of the 2011 Mw = 9.0 Tohoku-oki earthquake. Geophysical Research Letters, 38.   3. Selected_Stochastic_Samples.zip   This file includes a reduced sample space derived from the original stochastic samples, specifically selected for statistical analysis.   4. Sendai_1961.zip   This dataset contains the reconstructed morphology of the Sendai plain as it appeared in 1961. The reconstruction is based on aerial photographs provided by the Geospatial Information Authority of Japan (GSI).

opencc-by-4.0Aug 2021View details →

Results files for "End-to-end Bayesian analysis for summarizing sets of radiocarbon dates"

These are the results files for the following peer-reviewed article: Price, M.H., J.M. Capriles, J. Hoggarth, R.K. Bocinsky, C.E. Ebert, and J.H. Jones, (2021). End-to-end Bayesian analysis for summarizing sets of radiocarbon dates. Journal of Archaeological Science. They were generated inside a Docker container as outlined in the README of this github repository: https://github.com/MichaelHoltonPrice/price_et_al_tikal_rc The analyses rely on an R package located in this github repository: https://github.com/eehh-stanford/baydem For the results archived here, the commits for each repository are: <pre>price_et_al_tikal_rc 3ac1e35f4277ef878f8e3aac3d05159928a09a2b baydem 1220a60a860633b51f9f07cbff3eb78f458efc1a</pre>

publicNov 2024View details →

Diagnostic accuracy of nutritional screening tools in patients with digestive system tumors: A meta-analysis and bayesian evaluation dataset

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publicMar 2025View details →

Experimental and synthetic datasets supporting FITSA: Statistical analysis of fluorescence intensity transients with Bayesian methods

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publicJan 2020View details →

Bayesian network analysis of immune signaling networks FACS data

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publicMar 2020View details →

River dams and the stability of bird communities: A hierarchical Bayesian analysis in a tropical hydroelectric power plant

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opencc-zeroJul 2020View details →

Data from: Comparing traditional and Bayesian approaches to ecological meta-analysis

1. Despite the wide application of meta-analysis in ecology, some of the traditional methods used for meta-analysis may not perform well given the type of data characteristic of ecological meta-analyses. 2. We reviewed published meta-analyses on the ecological impacts of global climate change, evaluating the number of replicates used in the primary studies (ni) and the number of studies or records (k) that were aggregated to calculate a mean effect size. We used the results of the review in a simulation experiment to assess the performance of conventional frequentist and Bayesian meta-analysis methods for estimating a mean effect size and its uncertainty interval. 3. Our literature review showed that ni and k were highly variable, distributions were right-skewed, and were generally small (median ni =5, median k=44). Our simulations show that the choice of method for calculating uncertainty intervals was critical for obtaining appropriate coverage (close to the nominal value of 0.95). When k was low (<40), 95% coverage was achieved by a confidence interval based on the t-distribution that uses an adjusted standard error (the Hartung-Knapp-Sidik-Jonkman, HKSJ), or by a Bayesian credible interval, whereas bootstrap or z-distribution confidence intervals had lower coverage. Despite the importance of the method to calculate the uncertainty interval, 39% of the meta-analyses reviewed did not report the method used, and of the 61% that did, 94% used a potentially problematic method, which may be a consequence of software defaults. 4. In general, for a simple random-effects meta-analysis, the performance of the best frequentist and Bayesian methods were similar for the same combinations of factors (k and mean replication), though the Bayesian approaches had higher than nominal (>95%) coverage for the mean effect when k was very low (k<15). Our literature review suggests that many meta-analyses that used z-distribution or bootstrapping confidence intervals may have over-estimated the statistical significance of their results when the number of studies was low; more appropriate methods need to be adopted in ecological meta-analyses.

opennotspecifiedNov 2020View details →

FIGURE 20. Majority-rule consensus tree from Bayesian analysis using 16S in Revision of the French Polycirridae (Annelida, Terebelliformia), with descriptions of eight new species

FIGURE 20. Majority-rule consensus tree from Bayesian analysis using 16S. Asterisks indicate posterior probability> 90 %. Text in red refers to specimens sequenced during this study.

opencc-zeroJan 2021View details →

Data from: Association between metabolic syndrome components and the risk of developing nephrolithiasis: Bayesian meta-analysis and meta-regression with dose-response analysis

Nephrolithiasis has shifted to be a systemic disease. As opposed to an isolated urinary metabolic problem, it became determined that nephrolithiasis turned into considerably related to link with systemic diseases such as hypertension, obesity, dyslipidemia, and insulin resistance. The interplay between these four factors defines MetS (metabolic syndrome). In this review we aim to clarify the associations of metabolic syndrome and its components to kidney stone incident. Online databases of EMBASE, MEDLINE, and Google Scholar were searched up to October 2020 to identify observational studies examining the association between metabolic syndrome components and kidney stone incident. Bayesian Random-Effects Meta-Analysis and Meta-Regression were performed to observe the association. Linear dose-response analyses were conducted to shape the direction of the association. Data analysis was performed using STATA, and R statistics. This dataset contains supplementary material and figures as additional analysis of the study.

opencc-zeroDec 2017View details →

Data from: Phylogeny, macroevolutionary trends and historical biogeography of sloths: insights from a Bayesian morphological clock analysis

Sloths, like other xenarthrans, are an extremely interesting group of mammals that, after a long history of evolution and diversification in South America, became established on islands in the Caribbean and later reached North America during the Great American Biotic Interchange. In all three regions they were part of the impressive Pleistocene megafauna. Most taxa became extinct and only two small, distantly related tree-dwelling genera survived. Here we incorporate several recently described genera of sloths into an assembled morphological data supermatrix and apply Bayesian inference, using phylogenetic and morphological clock methods, to 64 sloth genera. Thus, we investigate the evolution of the group in terms of the timing of divergence of different lineages and their diversity, morphological disparity and biogeographical history. The phylogeny obtained supports the existence of the commonly recognized clades for the group. Our results provide divergence time estimates for the major clades within Folivora that could not be dated with molecular methods. Lineage diversity shows an early increase, reaching a peak in the Early Miocene followed by a major drop at the end of the Santacrucian (Early Miocene). A second peak in the Late Miocene was also followed by a major drop at the end of the Huayquerian (Late Miocene). Both events show differential impact at the family level. After that, a slight Plio-Pleistocene decline was observed before the marked drop with the extinction at the end of the Pleistocene. Phenotypic evolutionary rates were high during the early history of the clade, mainly associated with Mylodontidae, but rapidly decreased to lower values around 25 Ma, whereas Megalonychidae have lower values at the beginning followed by a steady increase, peaking during the Late Miocene and the Pliocene. Morphological disparity showed a similar trend, with an early increase, followed by a slowly increasing phase through the Late Oligocene and Early Miocene, and ending with another increase beginning at the middle of the Miocene. Biogeographic analysis showed southern South America as the most probable area of origin of the clade and the main region in which the early diversification events took place. Both Megatheriinae and Nothrotheriinae basal nodes were strongly correlated with Andean uplift events, whereas the early history of Mylodontidae is closely associated with southern South America and also shows an early occupation of the northern regions. Within Megalonychidae, our results show Choloepus as a descendant of an island dispersing ancestor and a probable re-ingression to South America by a clade that originated in Central or North America.

opencc-zeroDec 2012View details →

Data from: Bayesian analysis of biogeography when the number of areas is large

Historical biogeography is increasingly studied from an explicitly statistical perspective, using stochastic models to describe the evolution of species range as a continuous-time Markov process of dispersal between and extinction within a set of discrete geographic areas. The main constraint of these methods is the computational limit on the number of areas that can be specified. We propose a Bayesian approach for inferring biogeographic history that extends the application of biogeographic models to the analysis of more realistic problems that involve a large number of areas. Our solution is based on a 'data-augmentation' approach, in which we first populate the tree with a history of biogeographic events that is consistent with the observed species ranges at the tips of the tree. We then calculate the likelihood of a given history by adopting a mechanis- tic interpretation of the instantaneous-rate matrix, which specifies both the exponential waiting times between biogeographic events and the relative probabilities of each biogeographic change. We develop this approach in a Bayesian framework, marginalizing over all possible biogeographic histories using Markov chain Monte Carlo (MCMC). Besides dramatically increasing the number of areas that can be accommodated in a biogeographic analysis, our method allows the parameters of a given biogeographic model to be estimated and different biogeographic models to be objectively compared. Our approach is implemented in the program, BayArea.

opencc-zeroDec 2017View details →

Data from: Approximate Bayesian computation analysis of EST-associated microsatellites indicates that the broadleaved evergreen tree Castanopsis sieboldii survived the Last Glacial Maximum in multiple refugia in Japan

Climatic changes have played major roles in plants' evolutionary history. Glacial oscillations have been particularly important, but some of their effects on plants' populations are poorly understood, including the numbers and locations of refugia in Asian warm temperate zones. In the present study, we investigated the demographic history of the broadleaved evergreen tree species Castanopsis sieboldii (Fagaceae) during the last glacial period in Japan. We used approximate Bayesian computation (ABC) for model comparison and parameter estimation for the demographic modelling using 27 EST associated microsatellites. We also performed the species distribution modelling (SDM). The results strongly support a demographic scenario that the Ryukyu Islands and the western parts in the main islands (Kyushu and western Shikoku) were derived from separate refugia and the eastern parts in the main islands and the Japan Sea groups were diverged from the western parts prior to the coldest stage of the Last Glacial Maximum (LGM). Our data indicate that multiple refugia survived at least one in the Ryukyu Islands, and the other three regions of the western and eastern parts and around the Japan Sea of the main islands of Japan during the LGM. The SDM analysis also suggests the potential habitats under LGM climate conditions were mainly located along the Pacific Ocean side of coastal region. Our ABC-based study helps efforts resolve the demographic history of a dominant species in warm temperate broadleaved forests during and after the last glacial period, which provides a basic model for future phylogeographical studies using this approach.

opencc-zeroDec 2014View details →

Data from: Bayesian analysis of a morphological supermatrix sheds light on controversial fossil hominin relationships

The phylogenetic relationships of several hominin species remain controversial. Two methodological issues contribute to the uncertainty—use of partial, inconsistent datasets and reliance on phylogenetic methods that are ill-suited to testing competing hypotheses. Here, we report a study designed to overcome these issues. We first compiled a supermatrix of craniodental characters for all widely accepted hominin species. We then took advantage of recently developed Bayesian methods for building trees of serially sampled tips to test among hypotheses that have been put forward in three of the most important current debates in hominin phylogenetics—the relationship between Australopithecus sediba and Homo, the taxonomic status of the Dmanisi hominins, and the place of the so-called hobbit fossils from Flores, Indonesia, in the hominin tree. Based on our results, several published hypotheses can be statistically rejected. For example, the data do not support the claim that Dmanisi hominins and all other early Homo specimens represent a single species, nor that the hobbit fossils are the remains of small-bodied modern humans, one of whom had Down syndrome. More broadly, our study provides a new baseline dataset for future work on hominin phylogeny and illustrates the promise of Bayesian approaches for understanding hominin phylogenetic relationships.

opencc-zeroDec 2017View details →

Data from: FEATHER: automated analysis of force spectroscopy unbinding and unfolding data via a Bayesian algorithm

Single-molecule force spectroscopy (SMFS) provides a powerful tool to explore the dynamics and energetics of individual proteins, protein-ligand interactions, and nucleic acid structures. In the canonical assay, a force probe is retracted at constant velocity to induce a mechanical unfolding/unbinding event. Next, two energy landscape parameters, the zero-force dissociation rate constant (ko) and the distance to the transition state (Δx‡), are deduced by analyzing the most probable rupture force as a function of the loading rate, the rate of change in force. Analyzing the shape of the rupture force distribution reveals additional biophysical information, such as the height of the energy barrier (ΔG‡). Accurately quantifying such distributions requires high-precision characterization of the unfolding events and significantly larger data sets. Yet, identifying events in SMFS data is often done in a manual or semiautomated manner and is obscured by the presence of noise. Here, we introduce, to our knowledge, a new algorithm, FEATHER (force extension analysis using a testable hypothesis for event recognition), to automatically identify the locations of unfolding/unbinding events in SMFS records and thereby deduce the corresponding rupture force and loading rate. FEATHER requires no knowledge of the system under study, does not bias data interpretation toward the dominant behavior of the data, and has two easy-to-interpret, user-defined parameters. Moreover, it is a linear algorithm, so it scales well for large data sets. When analyzing a data set from a polyprotein containing both mechanically labile and robust domains, FEATHER featured a 30-fold improvement in event location precision, an eightfold improvement in a measure of the accuracy of the loading rate and rupture force distributions, and a threefold reduction of false positives in comparison to two representative reference algorithms. We anticipate FEATHER being leveraged in more complex analysis schemes, such as the segmentation of complex force-extension curves for fitting to worm-like chain models and extended in future work to data sets containing both unfolding and refolding transitions.

opencc-zeroDec 2015View details →

Bayesian analysis of resolved stellar spectra: application to MMT/Hectochelle observations of the Draco dwarf spheroidal

supplementary data products, including all sky-subtracted spectra from individual targets, as well as random draws from posterior PDFs for model parameters (see enclosed README file)

opennotspecifiedDec 2008View details →

FIGURE 7. Phylogenetic tree from Bayesian analysis. Thick branches indicate posterior probabilities over 80 in Revision of the Ranitomeya fantastica species complex with description of two new species from Central Peru (Anura: Dendrobatidae)

FIGURE 7. Phylogenetic tree from Bayesian analysis. Thick branches indicate posterior probabilities over 80.