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94 results for “methods: data analysis”
First-order phase transitions in Yang-Mills theories and the density of state method---data and analysis code release
<p>Data release for paper: Lucini, B., Mason, D., Piai, M., Rinaldi, E., & Vadacchino, D. (2023). First-order phase transitions in Yang-Mills theories and the density of state method. arXiv preprint arXiv:2305.07463.</p> <p>This data release comprises of:</p> <p>Importance sampling results: Input and output files for PureGauge file of HiRep (https://github.com/claudiopica/HiRep) and csv files contains analysis of results.</p> <p>LLR results: Input files for LLR_HB for a modified version of HiRep for the heat bath LLR algorthim with umbrella sampling (https://github.com/dave452/Hirep-LLR-SU) and some csv files containing analysis of output.</p> <p>Analysis code within the LLRAnalysis.zip, it contains the code and the conda environment.</p>
Data and Code Repository for Expanding non-target analysis methods to characterize the prenatal exposome
<p>Data and Code Repository for the following manuscript: Expanding non-target analysis methods to characterize the prenatal exposome. </p>
Data from: A new digital method of data collection for spatial point pattern analysis in grassland communities
Open the record for dataset details and reuse information.
Data for: Characterizing multi-criteria decision analysis, risk stratification, and hotspot analysis methods to optimise disease policymaking and evidence translation for medicines in low- and middle-income countries: A scoping review
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Time series methods for the analysis of soundscapes and other cyclical ecological data
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Data from: A method for analysis of phenotypic change for phenotypes described by high-dimensional data
The analysis of phenotypic change is important for several evolutionary biology disciplines, including phenotypic plasticity, evolutionary developmental biology, morphological evolution, physiological evolution, evolutionary ecology and behavioral evolution. It is common for researchers in these disciplines to work with multivariate phenotypic data. When phenotypic variables exceed the number of research subjects—data called 'high-dimensional data'—researchers are confronted with analytical challenges. Parametric tests that require high observation to variable ratios present a paradox for researchers, as eliminating variables potentially reduces effect sizes for comparative analyses, yet test statistics require more observations than variables. This problem is exacerbated with data that describe 'multidimensional' phenotypes, whereby a description of phenotype requires high-dimensional data. For example, landmark-based geometric morphometric data use the Cartesian coordinates of (potentially) many anatomical landmarks to describe organismal shape. Collectively such shape variables describe organism shape, although the analysis of each variable, independently, offers little benefit for addressing biological questions. Here we present a nonparametric method of evaluating effect size that is not constrained by the number of phenotypic variables, and motivate its use with example analyses of phenotypic change using geometric morphometric data. Our examples contrast different characterizations of body shape for a desert fish species, associated with measuring and comparing sexual dimorphism between two populations. We demonstrate that using more phenotypic variables can increase effect sizes, and allow for stronger inferences.
Data from: Convergence of multiple markers and analysis methods defines the genetic distinctiveness of cryptic pitvipers
Using multiple markers and multiple analytical approaches is critical for establishing species boundaries reliably, especially so in the case of cryptic species. Despite development of new and powerful analytical methods, most studies continue to adopt a few, with the choice often being subjective. One such example is routine analysis of Amplified Fragment Length Polymorphism (AFLP) data using population genetic models despite disparity between method assumptions and data properties. The application of newly developed methods for analyzing this dominant marker may not be entirely clear in the context of species delimitation. In this study, we use AFLPs and mtDNA to investigate cryptic speciation in the Trimeresurus macrops complex that belongs to a taxonomically difficult lineage of Asian pitvipers. We analyze AFLPs using population genetic, phylogenetic, multivariate statistical, and Bayes Factor Delimitation methods. A gene tree from three mtDNA markers provided additional evidence. Our results show that the inferences about species boundaries that can be derived from population genetic analysis of AFLPs have certain limitations. In contrast, four multivariate statistical analyses produced clear clusters that are consistent with each other, as well as with Bayes Factor Delimitation results, and with mtDNA and total evidence phylogenies. Furthermore, our results concur with allopatric distributions and patterns of variation in individual morphological characters previously identified in the three proposed species: T. macrops sensu stricto, T. cardamomensis, and T. rubeus. Our study provides evidence for reproductive isolation and genetic distinctiveness that define these taxa as full species. In addition, we re-emphasize the importance of examining congruence of results from multiple methods of AFLP analysis for inferring species diversity.
Data from: Comparative analysis of DNA extraction methods to study the body surface microbiota of insects: a case study with ant cuticular bacteria
High-throughput sequencing of the 16S rRNA gene has considerably helped revealing the essential role of bacteria living on insect cuticles in the ecophysiology and behavior of their hosts. However, our understanding of host-cuticular microbiota feedbacks remains hampered by the difficulties to working with low bacterial DNA quantities as in individual insect cuticle samples, which are more prone to molecular biases and contaminations. Herein, we conducted a methodological benchmark on the cuticular bacterial loads retrieved from two Neotropical ant species of different body size and ecology: Atta cephalotes (~15 mm) and Pseudomyrmex penetrator (~5 mm). We evaluated the richness and composition of the cuticular microbiota, as well as the amount of biases and contamination produced by four DNA extraction protocols. We also addressed how bacterial communities' characteristics would be affected by the number of individuals or individual body size used for DNA extraction. Most extraction methods yielded similar results in term of bacterial diversity and composition for A. cephalotes (~15 mm). In contrast, greater amounts of artifactual sequences and contaminations, as well as noticeable differences in bacterial communities' characteristics were observed between the extraction methods for P. penetrator (~5 mm). We also found that large (~15 mm) and small (~5 mm) A. cephalotes individuals harbor different bacterial communities. Our benchmark hence suggests that cuticular microbiota of single insect individuals can be reliably retrieved provided that blank controls, appropriate data cleaning, and standardization of individual body size are considered in the experiment.
Data from: Integrating complementary methods to improve diet analysis in fishery-targeted species
Developing efficient, reliable, cost-effective ways to identify diet is required to understand trophic ecology in complex ecosystems and improve food web models. A combination of techniques, each varying in their ability to provide robust, spatially and temporally explicit information can be applied to clarify diet data for ecological research. This study applied an integrative analysis of a fishery-targeted species group - Plectropomus spp.in the central Great Barrier Reef, Australia by comparing three diet-identification approaches. Visual stomach content analysis provided poor identification with ~14% of stomachs sampled resulting in identification to family or lower. A molecular approach was successful with prey from ~80% of stomachs identified to genus or species, often with several unique prey in a stomach. Stable isotope mixing models utilising experimentally-derived assimilation data, identified similar prey as the molecular technique but at broader temporal scales, particularly when prior diet information was incorporated. Overall, Caesionidae and Pomacentridae were the most abundant prey families (>50% prey contribution) for all Plectropomus spp., highlighting the importance of planktivorous prey. Less abundant prey categories differed among species/colour phases indicating possible niche segregation. This study is one of the first to demonstrate the extent of taxonomic resolution provided by molecular techniques, and, like other studies, illustrates that temporal investigations of dietary patterns are more accessible in combination with stable isotopes. The consumption of mainly planktivorous prey within this species group has important implications within coral reef foodwebs and provides cautionary information regarding the effects that changing resources could have in reef ecosystems.
Data from: Survival analysis and classification methods for forest fire size
Factors affecting wildland-fire size distribution include weather, fuels, and fire suppression activities. We present a novel application of survival analysis to quantify the effects of these factors on a sample of sizes of lightning-caused fires from Alberta, Canada. Two events were observed for each fire: the size at initial assessment (by the first fire fighters to arrive at the scene) and the size at "being held" (a state when no further increase in size is expected). We developed a statistical classifier to try to predict cases where there will be a growth in fire size (i.e., the size at "being held" exceeds the size at initial assessment). Logistic regression was preferred over two alternative classifiers, with covariates consistent with similar past analyses. We conducted survival analysis on the group of fires exhibiting a size increase. A screening process selected three covariates: an index of fire weather at the day the fire started, the fuel type burning at initial assessment, and a factor for the type and capabilities of the method of initial attack. The Cox proportional hazards model performed better than three accelerated failure time alternatives. Both fire weather and fuel type were highly significant, with effects consistent with known fire behaviour. The effects of initial attack method were not statistically significant, but did suggest a reverse causality that could arise if fire management agencies were to dispatch resources based on a-priori assessment of fire growth potentials. We discuss how a more sophisticated analysis of larger data sets could produce unbiased estimates of fire suppression effect under such circumstances.
Data from: Making soil particle size analysis by laser diffraction compatible with standard soil texture determination methods
The standard sieving, pipette and hydrometer methods for soil particle size analysis (PSA) have three main drawbacks: procedures are tedious, time-consuming, and the results are protocol-dependent. Laser diffraction PSA delivers rapid results using standardized procedures, but so far it has been difficult to reconcile results with those from standard sedimentation methods. The objective of this study was to develop a protocol that would permit direct usage of laser diffraction PSA and render results compatible with current methods. The protocol was developed using standard soil samples from different textural classes. Regression of the laser diffraction PSA against the hydrometer/pipette method yielded coefficients of determination of 0.92/0.9, 0.92/0.94 and 0.99/0.99, and root mean square errors of 0.04/0.05, 0.07/0.06 and 0.05/0.03 for clay, silt and sand, respectively. These statistics are comparable to those obtained by regressing results of the hydrometer against the sieve and pipette methods. A key factor in securing accurate and precise results was limiting the particle size range of the samples by wet sieving the sand fraction. This created representative samples and stable soil dispersed suspensions, allowing accurate estimations of particle size distribution for clay and silt fractions without empirical transformations. Results obtained with the proposed protocol matched those of standard sedimentation analyses for a wide range of soils, encouraging further adoption of laser diffraction for soil PSA.
Data from: Is computer-assisted instruction more effective than other educational methods in achieving ECG competence amongst medical students and residents? A systematic review and meta-analysis.
Objectives It remains unclear whether computer-assisted instruction (CAI) is more effective than other teaching methods in acquiring and retaining ECG competence amongst medical students and residents. Design This systematic review and meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Data sources Electronic literature searches of PubMed, databases via EBSCOhost, Scopus, Web of Science, Google Scholar and grey literature were conducted on 28 November 2017. We subsequently reviewed the citation indexes of articles identified by the search. Eligibility criteria Studies were included if a comparative research design was used to evaluate the efficacy of CAI versus other methods of ECG instruction, as determined by the acquisition and/or retention of ECG competence of medical students and/or residents. Data extraction and synthesis Two reviewers independently extracted data from all eligible studies and assessed the risk of bias. After duplicates were removed, 559 papers were screened. Thirteen studies met the eligibility criteria. Eight studies reported sufficient data to be included in the meta-analysis. Results In all studies, CAI was compared to face-to-face ECG instruction. There was a wide range of computer-assisted and face-to-face teaching methods. Overall, the meta-analysis found no significant difference in acquired ECG competence between those who received computer-assisted or face-to-face instruction. However, sub-analyses showed that CAI in a blended learning context was better than face-to-face teaching alone, especially if trainees had unlimited access to teaching materials and/or deliberate practice with feedback. There was no conclusive evidence that CAI was better than face-to-face teaching for longer-term retention of ECG competence. Conclusion CAI was not better than face-to-face ECG teaching. However, this meta-analysis was constrained by significant heterogeneity amongst studies. Nevertheless, the finding that blended learning is more effective than face-to-face ECG teaching is important in the era of increased implementation of e-learning. PROSPERO registration number CRD42017067054
Comparative analysis of statistical methods used for detecting differential expression in label-free mass spectrometry proteomics - Data Supplement
<p>This the is Data Supplement for the article "Comparative analysis of statistical methods used for detecting differential expression in label-free mass spectrometry proteomics" submitted to the Journal of Proteomics 2015.</p>
Data for A weak coupling mechanism for the early steps of the recovery stroke of myosin VI: a free energy simulation and string method analysis
<p>Representative frames, topology for MD simulation with NAMD and GROMACS, data and notebook to reproduce analyses in the paper "A weak coupling mechanism for the early steps of the recovery stroke of myosin VI: a free energy simulation and string method analysis" (Blanc, Houdusse, Cecchini, PLOS Computational Biology 2024).</p>
Data from: Identifying conservation priorities for gorgonian forests in Italian coastal waters with multiple methods including citizen science and social media content analysis
<div> <div> <div> <div> <p>Gorgonian forests are among the most complex of subtidal habitats in the Mediterranean Sea, supporting high biodiversity and providing diverse ecosystem services. Despite their iconic status, the geographical distribution and condition of gorgonian species is poorly known. Using multiple online data sources, our primary aims were to compile, map and analyse observations of gorgonian forests in Italian coastal waters to assess the biological complexity of gorgonian forests; evaluate impacts and vulnerable species, and identify areas of special interest inside and outside of existing MPAs to help prioritise conservation strategies and actions.</p> </div> </div> </div> </div>
Gene expression data from qPCR analysis of molting relevant genes in Calanus finmarchicus utilizing double delta-Ct method
<p>Gene expression data from qPCR analysis of molting relevant genes in Calanus finmarchicus utilizing double delta-Ct method for calculations of fold change and mean fold change. </p>
Data for "Technical reports: Methods - The Effects of Noise Magnitude and Measurement Resolution on Groundwater Tidal Analysis"
<p>This data for the technical note submitted to <em>Water Resources Research</em>.</p>
Data and analysis for "A process-conditioned and spatially consistent method for reducing systematic biases in modeled streamflow"
<p>This contains all of the necessary data and code to reproduce the results of the manuscript submitted to the Journal of</p> <p>Hydrometeorology entitled "A process-conditioned and spatially consistent method for reducing systematic biases in modeled streamflow"</p>
Data and code for "An open-source alignment method for multichannel infinite-conjugate microscopes using a ray transfer matrix analysis model"
<p>Original data and code associated with the paper "An open-source alignment method for multichannel infinite-conjugate microscopes using a ray transfer matrix analysis model".<br> <br> Further details on the data are available in the readme.txt files.</p>
Association Analysis for Chronic Diseases Based on Resident Health Records by Using Big Data Methods
ClinicalTrials.gov study NCT03279822. IPD Sharing: NO. Countries: 1. Publications: 2.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.