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1,249 results for “R data”
Data and R codes used in Delory et al (2017) F1000Research
<p>This repository contains all the data and R codes used for the use cases presented in Delory et al archiDART v3.0: a new data analysis pipeline allowing the topological analysis of plant root systems. The manuscript was submitted to F1000Research in December 2017.</p>
Data supplementing the article "Avoiding quantification bias in metabarcoding: application of a cell biovolume correction factor in diatom molecular biomonitoring" V. Vasselon, A. Bouchez, F. Rimet, S. Jacquet, R. Trobajo, M. Corniquel, K. Tapolczai, I. Domaizon submitted to Methods in Ecology and Evolution journal
<p>These data supplement the article "Avoiding quantification bias in metabarcoding: application of a cell biovolume correction factor in diatom molecular biomonitoring" V. Vasselon, A. Bouchez, F. Rimet, S. Jacquet, R. Trobajo, M. Corniquel, K. Tapolczai, I. Domaizon submitted to Methods in Ecology and Evolution journal</p> <p>The directory contains the following files:</p> <p>1<strong>5 fastq files raw reads (5 mock communities, 3 replicates)</strong><strong>.rar </strong>- contains the 15 fastq files provided by the sequencing platform with demultiplexed DNA reads (raw data prior any bioinformatics treatments).</p> <p><strong>15 fastq files information.xlsx</strong> :</p> <p>- contains the information relative to the 15 fastq files corresponding to the PGM raw data of the 5 mock communities (sequenced with 3 replicates), including: the ID of the fastq files, the mock community name, the replicate number, the final sample Id and the number of raw reads per fastq file.</p> <p>- contains the information of the proportion of the 8 diatoms species (%) used to create the 5 mock communities (estimated from microscopy).</p>
Telerobotic intergroup contact: Acceptance and preferences in Israel and Palestine - R Data and code.
<p>We present telerobotics as a novel form of intergroup contact to reduce prejudice and bring about positive social change between groups in conflict. Based on our previous conceptual framework and set of design hypotheses, we conducted a survey that confronts the theory with empirical data on acceptance and preferences of the telerobotic intergroup contact approach in Israel and Palestine. The results shed light on differences in attitudes between the groups and on design considerations for telerobotics when used for intergroup contact. The study serves as a foundation for implementing this novel method of technology-enhanced conflict resolution in the field.</p> <p>The data was analyzed in R software. The archive contains the survey data and the code analyses.</p> <p> </p> <p><em>The research is supported by The Kone Foundation</em></p>
MHC_DATA and R_CODE
<p><strong>Associations among MHC genes, latitude, and haemosporidian infections in the rufous-collared sparrow (</strong><i><strong>Zonotrichia capensis</strong></i><strong>)</strong></p>
Data set for ODI cricket matches from 1987 to 2023 (extracted from ESPN Cricinfo) and code (R) used for a statistical study
<p>Here I present the data and code that has been used to study the statistical evolution of ODI cricket. The preprint for this research is available at: </p> <div> <div> <div> <table> <tbody> <tr> <td><a href="https://doi.org/10.48550/arXiv.2406.11652">https://doi.org/10.48550/arXiv.2406.11652</a> <div><span>Focus to learn more</span></div> </td> </tr> </tbody> </table> </div> </div> </div> <div> </div>
Modeling data and R code for Chrysodeixis chalcites ecological niche
<p>The golden twin-spot moth, <em>Chrysodeixis chalcites</em> Esper (Lepidoptera: Noctuidae), is a polyphagous, polyvoltine crop pest occurring natively from northern Europe to Mediterranean Africa and the Canary Islands. Larvae feed on a wide variety of naturally occurring plants as well as soybean and other legume crops, short staple cotton, tomato, potato, peppers, tobacco, and banana. <em>Chrysodeixis chalcites</em> has been recorded in agricultural lands in the Ontario peninsula in eastern Canada and in northern counties of Indiana, USA. Given the strong potential for <em>C. chalcites</em> to invade USA crop lands, it is important to identify environments most likely to sustain growing populations of this pest. Though <em>C.</em> chalcites is native to Europe and North Africa, it has invaded sub-Saharan Africa. Using occurrence data form the native and invaded ranges, and environmental predictors including bioclimatic conditions and human disturbance, we trained three ecological niche models to estimate an ensemble prediction of environmental suitability in the contiguous US. Because human impact is potentially a confounding predictor, models were trained both with and without it. High environmental suitability was projected for the Atlantic coast from New England to Florida, the Gulf coast, the lower Midwest, and the Pacific coast and Central Valley of California.</p>
Example Data for the R package lpjmlkit (LPJmLData Vignette)
<div>This repository contains example data for the R package lpjmlkit to provide usable large datasets for LPJmLData Vignette.</div> <div> </div> <div><em>Breier, J., Ostberg, S., Wirth, S. B., Minoli, S., Stenzel, F., & Müller, C. (2024). lpjmlkit: Toolkit for Basic LPJmL Handling (Version 1.7.0) [Computer software]. https://doi.org/10.5281/zenodo.7773134</em></div> <div> </div> <div>Usage information: We split zip files to bypass Zenodo's upload restrictions. Please download all and open one of the zip files to unpack all automatically.</div>
Data Set for "Analyzing Microbial Growth with R"
<p>Sample data set used in "<a href="http://bconnelly.net/2014/04/analyzing-microbial-growth-with-r/">Analyzing Microbial Growth with R</a>"</p>
Assessing the Integrity of Older Archaeological Collections: An Example from La Ferrassie - supplemental material (data and R code)
<p>Supplemental data and R code for reproducing figures and table values in paper 'Assessing the Integrity of Older Archaeological Collections: An Example from La Ferrassie' by HL Dibble, SC Lin, DM Sandgathe, A Turq.</p>
Data and R code used in the preprint "Parasite intensity is driven by temperature in a wild bird" (doi 10.1101/323311)
<p>Data (as text files) and R code used in the preprint entitled "Parasite intensity is driven by temperature in a wild bird", recommended by <em>Peer Community In Ecology </em>(doi 10.1101/323311). See preprint and supplementary material; some explanations are also included in the R code. </p>
Data and R code associated to the publication: "Effects of land use, cover and protection on stream and riparian ecosystem services and biodiversity"
<p>This R code and dataset accompany Hanna et al's 2019 publication in Conservation Biology titled "Effects of land use, cover and protection on stream and riparian ecosystem services and biodiversity". Read the "Metadata" tab of the data file and code annotations for more information. </p>
Supplementary File S2 for the publication 'Predicting Bacterial Virulence Factors - Evaluation of Machine Learning and Negative Data Strategies' by Rentzsch, R et al.
<p>Supplementary File S2 for the publication 'Predicting Bacterial Virulence Factors - Evaluation of Machine Learning and Negative Data Strategies' by Robert Rentzsch, Carlus Deneke, Andreas Nitsche, and Bernhard Y. Renard</p>
Data and R code used in Delory et al (2019) When history matters: the overlooked role of priority effects in grassland overyielding
<p>This repository contains the raw data and R code used for the following paper: Delory et al (2019) When history matters: the overlooked role of priority effects in grassland overyielding.</p>
Data types and Variables in R
<p>This video explains how you store numbers, texts and logical variables in R using scalar and vector variables and also what are matrices and data frames and how we can utilize them in R.</p>
Post-revision data and R Script for Murtagh et al. 'The scent of enrichment: Exploring the effect of odour and biological salience on behaviour during enrichment of kennelled dogs.'
<p>Data and analysis file (written in R studio) for the paper Murtagh et al. 'The scent of enrichment: Exploring the effect of odour and biological salience on behaviour during enrichment of kennelled dogs.' Updated based on reviewer comments and additional analyses requested (master data and analysis filed labelled with 'rev' suffix).</p>
Data and R code used in Baudson et al (2019) Developmental plasticity of Brachypodium distachyon in response to P deficiency: modulation by inoculation with phosphate-solubilizing bacteria
<p>This repository contains the raw data and R code used for the following paper: Baudson et al (2019) Developmental plasticity of <em>Brachypodium distachyon</em> in response to P deficiency: modulation by inoculation with phosphate-solubilizing bacteria</p>
Applicability of the inverse dispersion method to measure emissions from animal housings - data set & R scripts
<h2>Data availability</h2> <p>Provided are:<br>- raw data of the instruments<br>- R Scripts to reproduce the findings in the publication<br>- R outputs</p> <h2>Scripts</h2> <p>In total, there are 10 scripts provided, of which most of them are needed to reproduce the data in the publication.</p> <p>Below, a brief explanation of the content of the different scripts.</p> <ul> <li>01_Datatreatment_01_Weatherstation.r ## This script reads in the weather station data and makes it ready for further use.</li> <li>01_Datatreatment_02_Sonics.r ## This script reads in the 3D ultrasonic data and makes it ready for further use.</li> <li>01_Datatreatment_03_GasFinder.r ## This script reads in the GasFinder data and makes it ready for further use.</li> <li>01_Datatreatment_04_MFC_Pressuresensor.r ## This script reads in the mass flow controller (MFC) and pressure sensor data and makes it ready for further use.</li> <li>02_Calculation_01_bLS.r ## This script is made to run the bLSmodelR and tailored to the number cruncher of the University of Applied Sciences BFH. The code should also work on your computer but you have to adopt the number of cores.</li> <li>02_Calculation_02_Concentration.r ## This script treats the unprocessed concentration data. It removes false concentrations, applies an intercalibration, and makes the data ready for further use.</li> <li>02_Calculation_03_Emissions.r ## This script calculates emissions and makes it ready for further use.</li> <li>02_Calculation_04_contourXYZ_Plume.r ## This script calculates the plume contours in the XY and XZ plane. This script is not necessary to reproduce the findings of the publication.</li> <li>03_Apply_filter.r ## This script applies the quality filtering and makes the data ready for further use.</li> <li>04_Plots_Tables.r ## With this script one can recreate all the plots and values in the tables of the publication, the supplement, and the initial submission.</li> </ul> <p>Note, for the geometry, there is no script provided. The coordinates of the different sensors and the source are solely provided as R output.</p> <h3>Naming of instruments</h3> <p>The instruments in the publication have different names than in the scripts. In some scripts the final names are also provided but throughout the evaluation the original device names are used. Only in the script 04_Plots_Tables.r are the final names introduced. Below is an overview of what original name corresponds to the final name of the devices:</p> <h4><strong>GasFinder instruments called 'OP' in the publication</strong></h4> <ul> <li>OP-UW = GF26</li> <li>OP-2.0h = GF17</li> <li>OP-5.3h = GF18</li> <li>OP-6.8h = GF16</li> <li>OP-12h = GF25</li> </ul> <p><strong>3D ultrasonic anemometer instruments called 'UA' in the publication</strong></p> <ul> <li>UA-UW = SonicC</li> <li>UA-2.0h = SonicA</li> <li>UA-5.3h = Sonic2</li> <li>UA-6.8h = SonicB</li> </ul> <p><strong>Source</strong><br>In some of the scripts, the source might be called 'Schopf' which is a local term for 'shed'.</p> <h2>Note</h2> <p>This code was written by Marcel Bühler (minor code chunks were originally written by Christoph Häni) and is intended to reproduce the findings of the linked publication. Please feel free to use and modify it (e.g., use it to run different dispersion models), but attribution is appreciated.</p> <h2>Disclaimer</h2> <p>I do not guarantee that everything works. It might be that not all variables were changed to English for better understanding correctly. Unfortunately, it is not possible to provide all the catalogs of the bLS run, as the total size is several 100s of GB. In case you run the bLS model on your own, the result will have a minimal difference, as no bLS run produces the same result twice. This should, however, not alter the findings.</p> <h2>Contact</h2> <p>In case you have questions, please contact Marcel Bühler (mb@bce.au.dk). In case this does not work, Christoph Häni might also be able to help (christoph.haeni@bfh.ch).</p>
Data files for siderite + R. palustris experiment
<p>Full dataset for the siderite + R. palustris experiment. Includes:</p> <ul> <li>Solution and pellet ferrozine assay data (Excel file)</li> <li>Raman data of samples and standards (Excel file)</li> <li>XRD data of samples and standards (Excel file)</li> <li>Normalized XAS absorption data for all standards used in Fe K-edge XANES (Excel file)</li> <li>Representative least-squares fits of 1) siderite-like (reduced) and 2) oxidized sample endmembers (Excel file)</li> </ul>
Dataset and R code for 'Do Morphometric Data Improve Phylogenetic Reconstruction? A Systematic Review and Assessment'
<p>Dataset of tree (.tre) files and R code for running generalized Robinson-Foulds distance (Smith, 2020a;b) analysis. </p> <p>The .tre files can be read into R (R Core Team., 2023) using the ape::read.tree function (Paradis et al., 2003), full details in R code file. </p> <p> </p> <p> </p> <p>Paradis, E., Claude, J., & Strimmer, K. (2004). APE: analyses of phylogenetics and evolution in R language. Bioinformatics, 20(2), 289-290. </p> <p>R Core Team. (2023). R: A Language and Environment for Statistical Computing. (Version 4.2.2). R Foundation for Statistical Computing, Vienna, Austria: https://www.R-project.org/. </p> <p>Smith, M. R. (2020a). Information theoretic generalized Robinson–Foulds metrics for comparing phylogenetic trees. Bioinformatics, 36(20), 5007-5013. https://doi.org/10.1093/bioinformatics/btaa614 </p> <p>Smith, M. R. (2020b). TreeDist: distances between phylogenetic trees. R package version 2.7.0. doi:10.5281/zenodo.3528124. </p>
Data and R code supporting Battison et al. (2024) New Phytologist
<p>Data and R code supporting Battison et al. (2024) <span><span>Tracking tree demography and forest dynamics at scale using remote sensing. </span></span>New Phytologist</p> <p>If using these data and/or R code in your work please cite the original publication listed above, as well as this repository using the corresponding DOI.</p> <p> </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.