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4,694 results for “data analysis”
A global expert elicitation on present-day human-fire interactions: data & analysis code
<p>These files support "A global expert elicitation on present-day human-fire interactions", accepted for publication in the Philosophical Transactions of the Royal Society B. doi: <span>10.1098/rstb.2023-0463</span></p> <p>The files contain data from a survey of experts on human-fire interactions as well as code used to process and analyse it.</p> <p>An overview of the files is given below. </p> <h2><strong>1) Data</strong></h2> <p>Raw survey data are provided by geographic region ("GFUS_region"). Data processed to produce analyses in the associated paper are provided as "GFUS_Processed".</p> <p>Columns in data files are named by the question of the survey that generated them (Q1b through Q90). The contents of the associated questions that were asked are given in the data_dictionary.xlsx file.</p> <p>- GFUS_spatial provides the data merged with a shapefile of the survey regions. </p> <p>- "Gov_compare" and "LIFE_SH_fire" provide files to compare survey data with the DAFI and LIFE literature meta-analyses (see Supplementary 3 to the main text).</p> <p>- Question meta-data and question-summary provides an overview of the questions, as well as a topline overview of the numbers of responses and internal coherence (entropy) of survey responses. </p> <h2>2) Code</h2> <p>4 scripts are provided. </p> <p>- Firstly the script that was used to summarise survey responses by geographic region (Summarise_by_region)<br>- Secondly the code used to conduct statistical tests presented in the paper<br>- Thirdly the code used to produce plots in the paper<br>- Fourthly the code used to produce topline descriptive statistics presented in the paper</p>
Source data of the MultiSTAAR manuscript "A statistical framework for multi-trait rare variant analysis in large-scale whole-genome sequencing studies".
<p>This dataset serves as the source data for Figures 2-3 and Extended Data Figures 1-2 of the MultiSTAAR manuscript titled "A statistical framework for multi-trait rare variant analysis in large-scale whole-genome sequencing studies". MultiSTAAR is a statistical framework and computationally-scalable analytical pipeline for functionally-informed multi-trait rare variant analysis in large-scale WGS studies.<br><br><strong>Figure 2.</strong> Manhattan plots and Q-Q plots for unconditional gene-centric coding, noncoding and ncRNA multi-trait analysis of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and triglycerids (TG) using TOPMed data (<em>n</em> = 61,838).<br><br><strong>Figure 3.</strong> TOPMed genetic region (2-kb sliding window) unconditional multi-trait analysis results of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and triglycerides (TG) using TOPMed data (<em>n</em> = 61,838).<br><br><strong>Extended Data Figure 1.</strong> Manhattan plots and Q-Q plots for unconditional gene-centric coding, noncoding and genetic region (2-kb sliding window) multi-trait analysis of fasting glucose (FG) and fasting insulin (FI) using TOPMed data (<em>n</em> = 21,731).<br><br><strong>Extended Data Figure 2.</strong> Manhattan plots and Q-Q plots for unconditional gene-centric coding, noncoding and genetic region (2-kb sliding window) multi-trait analysis of C-reactive protein (CRP), interleukin 6 (IL-6), lipoprotein-associated phospholipase A2 (Lp-PLA2) activity, and lipoprotein-associated phospholipase A2 (Lp-PLA2) mass using TOPMed data (<em>n</em> = 9,380).</p>
Raw Data and Analysis Codes for the Dynamic control of the NHSE manuscript
<p>Raw Data and Analysis Codes for the Dynamic control of the NHSE manuscript</p>
raw data - Effect of the decompression only compared to decompression with on lumbar degenerative spondylolisthesis: A meta-analysis
Open the record for dataset details and reuse information.
Data folders for OBRWR analysis on CIBNvsOS
<p>Data folder for CIBNvsOS</p>
Data for HPN-DREAM analysis using OBRWR and PHONEMeS
<p>Data for the HPN-DREAM analysis.</p>
Supplementary data: Optimising centralisation and decentralisation in distribution networks for perishable products through mathematical modelling, parametric analysis, and machine learning
<p><span>The success of distribution companies for perishable products is enabled by optimally configuring distribution networks, which allows for reducing total logistic costs while ensuring reduced product spoilage and high service levels. Since customer demand for perishable products varies over time, the network configuration should not be optimised once, but periodically reviewed. Among the decisions to be reviewed, determining whether to centralise or decentralise inventory (i.e., stock allocation in distribution centres) is crucial. However, the literature overlooks stock allocation decisions, and existing methodologies to compare the economic performance of centralised, decentralised, and hybrid policies neglect important cost items, also requiring advanced computational technologies and skills to be applied. This paper addresses these gaps by providing two contributions. In this dataset, a comparison has been made between the cost performance of centralized, decentralized, and hybrid stock allocation policies in distribution networks for perishable products. The dataset comprises 100,000 realistic case studies generated through a Sobol quasi-random low discrepancy series.</span></p>
GEM-MACH data for TOARII paper analysis for year 2015 v1.0.0
<p>GEM-MACH v3.1.43 sample data from TOARII paper, annual tropospheric ozone chemistry simulation. Monthly averaged surface plots for near surface(1.5M), and model hybrid levels at ~ 700 and 900 mb (hy indicates miodel hybrid data)</p>
Data and code supporting q2-boots manuscript analysis
<div> <div>This record contains data, code, and analysis results for the Raspet et al. q2-boots manuscript. The q2-boots zip file contains the version of the code that was used to perform the analyses presented in the manuscript (commit hash: 1c32499620843de4775ff704d751f6dbd1ce524e). </div> </div>
MATLAB results files of MS-based analysis and raw photometer data - Systematic identification of allosteric effectors in Escherichia coli metabolism
<p>MATLAB result tables from progress curve analysis for each of the 19 enzymes tested with 79 potential effectors metabolites in MS-based approach. Excel tables with labelled photometer data.</p>
Raw GC-ToF-MS and processed data from individuals sampled in allopatric and contact zones and MZmine 3.9.0 and Rstudio analysis
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Data from: A densely sampled nuclear phylogenomic analysis of the coryphoid palms (Arecaceae − Coryphoideae)
<p><strong>Data from:</strong></p> <p>Wrisberg, O, Petoe, P, de Lima Ferreira, P, Bacon, CD, Barfod, AS, Bellot, S, Cano, Á, Couvreur, TLP, Dransfield, J, Henderson, A, Stauffer, F, Baker, WJ, Eiserhardt, WL (in review) <strong>A densely sampled nuclear phylogenomic analysis of the coryphoid palms (Arecaceae − Coryphoideae)</strong></p> <p>This repository is meant to provide the most important data outputs produced by the Pipeline created for this project. The analysis pipeline is located on github (https://github.com/pebgroup/coryphoideae_species_tree). Raw data can be found on the NCBI Sequence Read Archive. </p> <p>The data folder is divided into the following subfolders:</p> <p><strong>01_unaligned_sequences_per_specimen</strong></p> <p>This folder contains the unaligned sequences for each specimen. The sequences are named after the specimen number.</p> <p><strong>02_unaligned_sequences_per_gene</strong></p> <p>This folder contains the unaligned sequences for each gene. The sequences are named after the gene name.</p> <p><strong>03_aligned_sequences_per_gene</strong></p> <p>This folder contains the sequences aligned by MAFFT for each gene. The sequences are named after the gene name.</p> <p><strong>04_gene_trees</strong></p> <p>This folder contains the gene trees for each gene. The trees are named after the gene name. The subfolder <strong>subset_single_copy_gene_trees</strong> contains copies of the gene trees for the single copy genes.</p> <p><strong>05_species_trees</strong></p> <p>This folder contains the species trees. The subfolder <strong>all_genes</strong> contains the species trees based on all genes, while the subfolder <strong>single_copy_genes</strong> contains only the species trees based on the single copy genes.</p> <p><strong>06_supporting_information</strong></p> <p>This folder contains a list which contains the associations between tip names and specimen numbers and a list of the single-copy genes.</p>
Raw data and R code for the stone artifact analysis in "Lithic miniaturization in South China since the terminal Pleistocene: a multivariate analysis of lithic reduction from Fodongdi, Fulin and Xiqiaoshan"
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Three-Dimensional Segmentation Assisted with Clustering Analysis for Surface and Volume Measurements of Equine Incisor in Multidetector Computed Tomography Data Sets
<p>The dataset contains computed tomography (CT) images of head horses with annotations of 12 segments corresponding to areas with teeth. Imaged animals: 49 horses. Measured animal features such as surface area, and volume are included. The study was supported by the National Science Centre, Poland as a part of the project<br>Miniatura 6 No 2022/06/X/ST6/00431. </p>
Spatio-temporal analysis of remotely sensed forest loss data in the Cordillera Administrative Region, Philippines
<p>The Cordillera Administrative Region (CAR) in the Philippines is among the last forest frontiers in the country and is also home to 13 major watersheds in Northern Luzon that supply irrigation and hydroelectricity to other regions. However, it is faced with the deterioration of the quality of its watersheds due to forest loss driven mainly by agricultural expansion and illegal logging. Thus, this study was conducted to analyze the spatial and temporal patterns of forest loss that could serve as a basis for policy decisions. Also, this paper determined the strength of relationships using Pearson's correlation coefficient (<i>r</i>) between forest loss and seven independent variables, which includes forest cover, agricultural areas, built-up, road network, and socio-economic data. This study utilized the Hansen Global Forest Change (HGFC), a Landsat-derived dataset from 2001 to 2019. Results revealed that 70,925 hectares (ha) of forest loss were detected with an annual deforestation rate of 3,744 ha/year across the region. Based on the validation, the accuracy of the HGFC data is 72%, but great caution should be observed when using the data with less than 0.2 ha due to very low accuracy. On a region-wide analysis, only the forest cover had a strong association with the forest loss with a computed <i>r-value</i> of 0.78. Conversely, on a provincial level, the explanatory variables had a strong to moderately strong correlation with deforestation. Hence, immediate, science-based, and sustained regional and multi-stakeholder efforts are necessary to conserve and protect the remaining forest cover in the region.</p>
Fleshy red algae mats act as temporary reservoirs for sessile invertebrate biodiversity - Raw data for biodiversity analysis, species list and detailed output data from iNEXT procedure
<p>Raw data for biodiversity analysis, species list and detailed output data from iNEXT procedure for manuscript entitled "Fleshy red algae mats act as temporary reservoirs for sessile invertebrate biodiversity".</p>
Data for behavioral state-dependent habitat selection analysis of translocated female greater sage-grouse, North Dakota 2018-2020
<p>This dataset is associated with the article, "Behavioral state-dependent habitat selection and implications for animal translocations" (Picardi et al., 2021, Journal of Applied Ecology).</p> <p>Post-release monitoring of translocated animals can be used to inform future translocation protocols. In particular, quantifying habitat selection of translocated individuals may help identify features that characterize suitable settlement habitat and inform the choice of future release sites; however, because translocated animals undergo post-release behavioral modification, the underlying behavioral state needs to be taken into account.</p> <p>We analyzed behavioral state-dependent habitat selection in female greater sage-grouse (<i>Centrocercus urophasianus</i>) translocated from Wyoming to North Dakota, USA, using Hidden Markov Models in combination with Integrated Step Selection Analysis. This dataset includes GPS tracks (resampled at a 6-hour resolution using a Continuous Time Movement Model) for 48 individuals translocated between 2018 and 2020, along with environmental variables associated with each location. We segmented each track into behavioral phases corresponding to an exploratory state, characterized by broad and directed movements, and a restricted state, characterized by short and tortuous movements. Then, we quantified habitat selection in each state while also accounting for seasonality and individual reproductive status.</p> <p>Habitat selection of translocated sage-grouse differed between the post-release exploration and the settlement phase. While in the exploratory state, sage-grouse exhibited natal habitat preference induction by selecting for high sagebrush cover, typical of their natal area but not of the release area. In the restricted state, sage-grouse selected for gentle topography and also adjusted their habitat selection based on the season and their reproductive needs.</p>
ECMWF operational analysis data for driven the WRF model in HRB
<p>All the ECMWF operational analysis data forcing data (2008-2012) related to the thesis (<a href="https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/deliver/index/docId/81907/file/PhD_Zhang.pdf">https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/deliver/index/docId/81907/file/PhD_Zhang.pdf</a>)</p> <p> </p> <p> </p>
Data and analysis for: Divergent occurrences of juvenile and adult trees are explained by both environmental change and ontogenetic effects
<p>This is a mirror of the github repository https://github.com/lukasheiland/Divergence at 2021-12-16, which provides code and aggregated data to reproduce the simulations and analyses in "Divergent occurrences of juvenile and adult trees are explained by both environmental change and ontogenetic effects". Session info is provided in 'DEF_sessionInfo__2020-11-02.*'.</p> <p>The simulations are contained in<br> - 'Sim ontogenetic stages.R'</p> <p>The main script for the empirical analysis<br> - 'Fit beta.R' performs the complete analysis with already aggregated data that is provided with 'Data/taxtables_pres_thresholdsubset.rds'.</p> <p>In addition, several other scripts are provided for reference, which can be explored interactively, but would need additional unanomyzed data to be run completely:<br> - 'Prepare data.R' had been run for wrangling the unanonymized data prior to the analysis.<br> - 'Publishing/Publish fit.R' creates maps, plots, and tables. (For maps, original coordinates would be necessary.)<br> </p>
Factors hampering and facilitating RRI: finds from the analysis of data from four H2020 SwafS CSAs
<p>List of finds regarding factors that facilitate or hamper RRI-oriented change derived from the analysis of data from four relevant H2020 SwafS CSAs, namely GRACE, FIT4RRI, Starbios2, and Resbios</p>
ScienceDex guides
Understand access before you commit
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.