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172 results for “R script”
Datasets and R-scripts used for the revision of the Dibrachys cavus complex by Peters & Baur, 2011, Zootaxa 2937.1
<p>In 2011 we published a revision on the Dibrachys cavus complex in Zootaxa (Peters and Baur, 2011, here a link to our <a href="https://doi.org/10.11646/zootaxa.2937.1.1">open access paper</a>). It was our wish to also publish two versions of the dataset (one with missing values, one with missing values imputed) as supplementary files. Unfortunately, the data files seem to be no longer available on the publishers webpage. Hence, we publish the data files herewith again in CSV format.</p> <p>We take the opportunity to also publish the R-scripts that we used for calculating multivariate analyses, tests, and the multiple imputation of missing values.</p> <p>All files are available individually and with an own link. For convenience, we have compiled all files also in a ZIP file.</p> <p><a href="https://doi.org/10.5281/zenodo.4256704">Baur (2020)</a> used the dataset for further exploration in a Multivariate Ratio Analysis (MRA).</p> <p>Papers quoted above you may find in the section <em>References</em> of the Zenodo package.</p> <p><strong>Citation of this package</strong><br> Peters, Ralph S., & Baur, Hannes (2020, November 9) Datasets and R-scripts used for the revision of the Dibrachys cavus complex by Peters & Baur, 2011, Zootaxa 2937.1. Zenodo. https://doi.org/10.5281/zenodo.4264539 (directs to the newest version of the package).</p>
Data, scripts, and R Notebook for Carneiro et al 2023. Flight performance and wing morphology in the bat Carollia perspicillata: biophysical models and energetics. Integrative Zoology DOI:10.1111/1749-4877.12707
<p>Files provided as supporting information for the paper by Carneiro et al. 2023. Flight performance and wing morphology in the bat <em>Carollia perspicillata</em>: biophysical models and energetics. Integrative Zoology. DOI:10.1111/1749-4877.12707</p> <p>File descriptions</p> <p>ArmTA.txt - Temperature and surface areas for arms of <em>C. perspicillata</em> after flight experiment<br> BodyTA.txt - Temperature and surface areas for body of <em>C. perspicillata</em> after flight experiment<br> HeadTA.txt - Temperature and surface areas for head of <em>C. perspicillata</em> after flight experiment<br> WingTA.txt - Temperature and surface areas for wings (patagium) of <em>C. perspicillata</em> after flight experiment<br> WingMorph.txt - Morphological variables measured in the body and wings of <em>C. perspicillata</em><br> HeatLoss.R - Function to estimate heat loss (Qt)<br> PowFlight.R - Function to estimate minimum power required to fly<br> Script-HeatLoss-FlightPerformance.R - R script with set of analyses performed<br> SupportingInformationFile.docx - R notebook with set of analyses performed, word format<br> SupportingInformationFile.nb.html - R notebook with set of analyses performed, html format<br> SupportingInformationFile.Rmd - R notebook with set of analyses performed (R markdown)</p> <p>For the R scripts (Script-HeatLoss-FlightPerformance.R) and notebook (<br> SupportingInformationFile.Rmd) to work and be compiled, all files need to be copied to the same folder.</p>
R script and data files for Oakley et al (2017) Journal of Proteome Research. DOI: 10.1021/acs.jproteome.6b00797
<p>This R script and data replicates the analysis of Oakley et al (2017) Thermal shock induces host proteostasis disruption and endoplasmic reticulum stress in the model symbiotic Cnidarian <em>Aiptasia</em>. <em>Journal of Proteome Research</em>. 16:2121-2134. DOI: 10.1021/acs.jproteome.6b00797. </p>
Dataset and R script for the analysis in the article "Food waste between environmental education, peers, and family influence. Insights from primary school students in Northern Italy", Journal of Cleaner Production
<p>We hereby publish the dataset (with metadata) and the R script (R Core team, 2018) used for implementing the analysis presented in the paper "Food waste between environmental education, peers, and family influence. Insights from primary school students in Northern Italy", <em>Journal of Cleaner Production </em>(Piras et al., 2023). The dataset is provided in csv format with semicolons as separators and "NA" for missing data. The dataset includes all the variables used in at least one of the models presented in the paper, either in the main text or in the Supplementary Material. Other variables gathered by means of the questionnaires included as Supplementary Material of the paper have been removed. The dataset includes inputted values for missing data on independent variables. These were inputted using two approaches: last observation carried forward (LOCF) - preferred when possible - and last observation carried backward (LOCB). The metadata are presented as a PDF file.</p>
Data and R-Scripts for "Quality and timing of crowd-based water level class observations"
<p>This are the data and the R-scripts used for the manuscript "Quality and timing of crowd-based water level class observations" accepted for publication in the journal Hydrological Processes in July 2020 as a Scientific Briefing. To run the code, just run the R-script with the name "RunThisForResults.R". Results will be written to the "Figures" and the "Results" folder.</p>
Data and R script for 'Evaluating the cyclic ratio schedule as an assay of feeding behaviour in the European starling (Sturnus vulgaris)'
<p>Data files and R script for Dunn et al. "Evaluating the cyclic ratio schedule as an assay of feeding behaviour in the European starling (<em>Sturnus vulgaris</em>)"</p> <p>Includes a single R script that produces all the analyses in the paper. The script makes use of three different .csv data files.</p>
SLAFEEL: R scripts and reformatted data analyzed by Alamil et al. (2019)
<p>SLAFEEL: Statistical Learning Approach For Estimating Epidemiological Links from deep sequencing data</p> <p>This archive contains R scripts for running analyses proposed by Alamil et al. (2019; Inferring epidemiological links from deep sequencing data: a statistical learning approach for human, animal and plant diseases), namely<br> - functions.R that contains R functions required for computations,<br> - influenza.R, ebola.R and potyvirus.R where the analyses are implemented for each case study, and<br> - influenza-format-genomic-data.R giving an example of how to format data to be used in the statistical learning approach.</p> <p>This archive also contains the reformatted data analyzed by Alamil et al. (2019). The datasets that are provided concern swine influenza virus (reformatted from Murcia et al., 2012), Ebola virus (reformatted from Gire et al., 2014) and a wild salsify potyvirus. Two rds files are provided for swine influenza, the first one for the naive chain, the second one for the vaccinated chain. Ebola rds files are compressed into the archive ebolaRDS.zip. rds files can be loaded in the R statistical software with the command "readRDS(filename)", which returns a list. The list contains a "readme" item describing the contents of the list, as well as a "host.table" item providing metadata about host units and a "set.of.sequences" item providing sequencing data formatted in numeric matrices.</p> <p>Murcia PR, Hughes J, Battista P, Lloyd L, Baillie GJ, Ramirez-Gonzalez RH, et al. Evolution of an Eurasian avian-like influenza virus in naive and vaccinated pigs. PLoS Pathogens. 2012;8(5):e1002730.</p> <p>Gire SK, Goba A, Andersen KG, Sealfon RS, Park DJ, Kanneh L, et al. Genomic surveillance elucidates Ebola virus origin and transmission during the 2014 outbreak. Science. 2014;345:1369–1372</p> <p> </p> <p>Funded by the ANR - Project name: SMITID (2016-2020) - Grant number: ANR-16-CE35-0006</p>
R scripts for analyzing LiDAR data to assess forest canopy structure and perform Principal Component Analysis (PCA) on derived metrics
<p>This repository contains R scripts for analyzing LiDAR data to assess forest canopy structure and perform Principal Component Analysis (PCA) on spectral and LiDAR-derived metrics. The scripts cover LiDAR data processing, canopy height model (CHM) generation, calculation of forest canopy metrics, and PCA analysis.</p>
Data and R-scripts for "Land-use trajectories for sustainable land system transformations: identifying leverage points in a global biodiversity hotspot" (V2)
<p>Sustainable land system transformations are necessary to avert biodiversity and climate collapse. However, it remains unclear where entry points for transformations exist in complex land systems. Here, we conceptualize land systems along land-use trajectories, which allows us to identify and evaluate leverage points; i.e., entry points on the trajectory where targeted interventions have particular leverage to influence land-use decisions. We apply this framework in the biodiversity hotspot Madagascar. In the Northeast, smallholder agriculture results in a land-use trajectory originating in old-growth forests, spanning forest fragments, and reaching shifting hill rice cultivation and vanilla agroforests. Integrating interdisciplinary empirical data on seven taxa, five ecosystem services, and three measures of agricultural productivity, we assess trade-offs and co-benefits of land-use decisions at three leverage points along the trajectory. These trade-offs and co-benefits differ between leverage points: two leverage points are situated at the conversion of old-growth forests and forest fragments to shifting cultivation and agroforestry, resulting in considerable trade-offs, especially between endemic biodiversity and agricultural productivity. Here, interventions enabling smallholders to conserve forests are necessary. This is urgent since ongoing forest loss threatens to eliminate these leverage points due to path-dependency. The third leverage point allows for the restoration of land under shifting cultivation through vanilla agroforests and offers co-benefits between restoration goals and agricultural productivity. The co-occurring leverage points highlight that conservation and restoration are simultaneously necessary. Methodologically, the framework shows how leverage points can be identified, evaluated, and harnessed for land system transformations under the consideration of path-dependency along trajectories.</p>
Harmfull algae bloom monitoring program dataset; ERDDAP, ERA5 and ONI datasets; and R script for multicriteria analisys in Santa Catarina coastal zone, Brazil.
<p>Project Harmful Algae Bloom (HAB) Monitoring Network in Santa Catarina, Brazil - Database and R script with data analysis. This project was funded by the Foundation for Research Support of the State of Santa Catarina – FAPESC and generated a database combining a HAB monitoring dataset with oceanographic (from ERDDAP) and climatic (from ERA5 and ONI) data which was submitted to multicriteria analysis using R. The HAB monitoring dataset was obtained from Cidasc/SC State Government (http://www.cidasc.sc.gov.br/defesasanitariaanimal/monitoramento-de-algas-nocivas/) and contains results of phytoplankton counts in water samples and toxin levels in shellfish samples obtained from 39 points located in shellfish farms distributed along the SC coastline. Oceanographic data were obtained from the ERDDAP/NOAA website (https://coastwatch.pfeg.noaa.gov/erddap/index.html), including the variables mean chlorophyll concentration (mg.m-3) and mean sea surface temperature (ºC); Climate data were obtained from Copernicus/ERA5 (https://cds.climate.copernicus.eu/) including the variables mean air temperature (ºC), mean pressure (Pasc.), mean cloud cover (%), mean precipitation (kg.m-2), radiation (Einsteins.m-2.day-1), mean U wind (m.s-1), and mean V wind (m.s-1).; Oceanic Niño Index (ONI) data were obtained from the NOAA website (https://origin.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ONI_v5.php); The R script involves a pre-processing routine aimed at summarizing and integrating all datasets and the subsequent data analyses carried out to evidence temporal patterns related to different type of algal blooms. Detailed methods will be provided in a scientific article.</p>
Data and R scripts for KCC plots in Douville and Willett (2023)
<p>CMIP6 data (historical and scenario SSP5-8.5, run 1 only), observation and R scripts to plot Fig.1 and Fig.2 of Douville and Willett (Sc. Adv., 2023)</p>
Data and R scripts for analyses of declines in invertebrate species from the Gulf of Maine, USA, 1997 - 2018
Data files and R scripts are for the analyses that are presented in an article that is under revision for Biology Communications. The title of the article is: Declines over the last two decades of five key invertebrate species found on rocky intertidal shores throughout the western North Atlantic. The three data files contain the abundances of four gastropod species and the recruitment of barnacles and mussels from 1997 to 2018, monthly temperature data from three buoys from 2001 to 2018, and pH and aragonite saturation state from 1997 to 2014. R scripts include details of Bayesian estimates for Poisson regressions of species over time, clean-up of environmental data, imputation of missing environmental data and analyses of species versus environmental parameters.
Transgenerational plasticity of inducible defenses: combined effects of grand-parental, parental and current environments - PDF, datasets and R script
<p><strong>PDF, dataset and R script for the paper:</strong></p> <p>Tariel J, Plénet S, & Luquet E. <em>Transgenerational plasticity of inducible defenses: combined effects of grand-parental, parental and current environments</em>. </p> <p>Two data sets are provided: one for the analysis of the behavior (dataBehaviour.csv) and one for the analysis of other variables (weight, shell thickness and morphology; dataMorphology.csv). There are analyzed in the same R script (Script_TARIEL-Juliette.R)</p> <p><strong>Signification of variables names:</strong></p> <p>G1: treatment/environment of the grand-parental generation (control C or with predator-cue P)<br> G2: treatment/environment of the parental generation (control C or with predator-cue P)<br> G3: treatment/environment of the offspring generation (control C or with predator-cue P)<br> Family: unique ID for each family<br> Individual: number to identify siblings within a family <br> ID: unique ID for each individual <br> W: snail total weight (g)<br> Th: shell thickness (mm)<br> L: shell length (mm)<br> l: shell width (mm)<br> Lo: aperture length (mm)<br> lo: aperture width (mm)<br> crawlout : position of the snail (0: below the water surface; 1: above/on the water surface)<br> Day : day of measurement (crawling-out behaviour was measured three times through three consecutives days d2, d3 and d4)</p>
Dataset and R-script for simple mechanistic model of Heracleum sosnowskyi seed dispersal by wind
<p>The dataset contains:</p> <p>- primary data about Heracleum sosnowskyi seeds traits (terminal velocity, mass, area, wing loading) and release heights for <em>H. sosnowskyi</em> populations from two geographically distant Russia regions;</p> <p>- results of experiments of model seeds launches under different wind speeds;</p> <p>- R script for exploratory statistical analysis, linear regressions and mechanistc models testing.</p> <p>The anemochorous seed dispersal was generalized with a number of empirical and mechanistic models of varying complexity. The aim of this work was to develop the simplest possible mechanistic model of <em>Heracleum sosnowskyi</em> that allows to determine the distance of seed dispersal by wind with an accuracy comparable to that of empirical measurements. We measured and compared the characteristics of the seeds (terminal velocity, mass, area, wing loading) as well as the release height for <em>H. sosnowskyi</em> populations from two geographically distant Russia regions. We tested two simplest mechanistic models: a ballistic model and a wind gradient model using identical artificial seeds with characteristics similar to those of real <em>H. sosnowskyi</em> seeds. The wind gradient model gave the best results, despite the fact that uniform in shape, weight and size artificial <em>H. sosnowskyi</em> seeds, when dropped simultaneously from the same height, fly off at different distances. This model provides an estimate of dispersal distances with an accuracy comparable to that of empirical measurements. We plan to use the presented model to develop an individual-based model that will allow us to calculate the flight distances of <em>H. sosnowskyi</em> propagules, taking into account real weather conditions in different years and in different parts of its invasion range. All primary data and R-scripts used are freely available at the Zenodo repository (https://doi.org/10.5281/zenodo.3766035).</p> <p> </p>
Data and R-script for a tutorial that explains how to convert spreadsheet data to tidy data.
<p>Data and R-script for a tutorial that explains how to convert spreadsheet data to tidy data. The tutorial is published in a blog for The Node (https://thenode.biologists.com/converting-excellent-spreadsheets-tidy-data/education/)</p>
R script for identification and localisation of prophage within bacterial genomes using outward-oriented paired-end reads.
<p>This R script shows an analysis example of using outwards-oriented paired-end reads (OPRs), identified using the OPR finder function in the mVIRs package, to identify p22 in <em>S</em>. Tm LT2 as described in the publication "<strong>High throughput sequencing provides exact genomic locations of inducible prophages and accurate phage-to-host ratios in gut microbial strains" </strong>by Zünd et al. Microbiome (2021)</p>
Collapse and Continuity: A multi-proxy reconstruction of settlement organization and population trajectories in the Northern Fertile Crescent during the 4.2kya Rapid Climate Change event (dataset and R scripts)
<p>The present digital archive is the outcome of the paper: <strong>Lawrence, D., Palmisano, A., and de Gruchy, M.W., 2021. <a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0244871">Collapse and Continuity: A multi-proxy reconstruction of settlement organization and population trajectories in the Northern Fertile Crescent during the 4.2kya Rapid Climate Change event</a></strong><a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0244871">.</a> <em><strong>PLoS ONE</strong></em><strong>,</strong> <strong><em>16</em></strong>(1).</p> <p>The dataset included here provides a collection of <strong>920 </strong>radiocarbon dates and <strong>1070</strong> sites from archaeological surveys. In addition, the digital archive related to this paper provides reproducible analyses in the form of three scripts written in R statistical computing language.</p>
Holocene regional population dynamics and climatic trends in the Near East: a first comparison using archaeo-demographic proxies (dataset and R scripts)
<p>The present digital archive is the outcome of the paper: <strong>Palmisano, A., Lawrence, D., de Gruchy, M.W., Bevan, A., and Shennan, S., 2021. <a href="https://doi.org/10.1016/j.quascirev.2020.106739">Holocene regional population dynamics and climatic trends in the Near East: a first comparison using archaeo-demographic proxies</a>. <em>Quaternary Science Reviews</em>, <em>252</em></strong>.</p> <p>The dataset included here provides a collection of <strong>10,606</strong> radiocarbon dates, <strong>1884</strong> sites from archaeological surveys (1336 from Central Anatolia and 478 from Upper Mesopotamia) and <strong>16</strong> palaeoclimatic records for a period spanning between 14,000 and 2500 BP. In addition, the digital archive related to this paper provides reproducible analyses in the form of four scripts written in R statistical computing language.</p> <p>List of versions:</p> <ul> <li><strong>2.0.</strong> 15 December 2020 — Includes a few minor error corrections (the files 'References.txt' within the folder csv and the script 'radiocarbon.R').</li> <li><strong>1.0</strong> 28 November 2020 — First public release of the dataset on Zenodo.</li> </ul>
Data and R script for Neville, Andrews, Nettle and Bateson, 'Dissociating the effects of alternative early-life feeding schedules on the development of adult depression-like phenotypes'
<p>The R script and raw data files for the paper 'Dissociating the effects of alternative early-life feeding schedules on the development of adult depression-like phenotypes', by Vikki Neville, Clare Andrews, Daniel Nettle and Melissa Bateson.</p>
Dataset and full R script used in the data analysis of the paper "Overlooked and undervalued: Peripheral pollinators in an urban network"
<p>Dataset and full R script used in the data analysis of the paper "<strong>Overlooked and undervalued: Peripheral pollinators in an urban network</strong>".</p> <p>Summary:</p> <p>Since insect pollinators are essential for their ecological and agricultural roles, their conservation should be a priority, particularly in the remnant green spaces within highly urbanised cities. To gain insight into the occurrence of interactions between plants and often overlooked pollinators, and into their requirements for persistence over time in urban green spaces, we studied flower visitor diversity associated with a remnant of native vegetation in Cordoba (Argentina), one of the largest cities in South America. We recorded 198 insect species from six orders (Hymenoptera, Diptera, Lepidoptera, Coleoptera, Thysanoptera, and Hemiptera) interacting with the flowers of 94 plant species. The plant-pollinator interaction network was significantly modular, with 178 pollinators playing a peripheral role (i.e., it has a few links inside its own module and rarely any to other modules). We focused on the life history traits of these peripheral pollinators, which are often neglected in ecological studies. We classified their requirements to complete the life cycle and to persist over time into three broad categories: floral rewards, places to reproduce, and additional resources for food and nests. The life cycle requirements of peripheral pollinators differ significantly across insect orders. Hymenoptera and Lepidoptera have distinct life history requirements while Diptera and Coleoptera overlap in resource use. The three life history categories highlight how pollinators displayed different foraging behaviour, reproductive strategies of immature and adult stages, and the requirement of additional food resources used by larvae and adults beyond flower rewards to complete their life cycles. Knowledge about the requirements of neglected pollinators is a benchmark that can help to identify where efforts need to be made to conserve and maintain their biodiversity, even in small urban green spaces.</p>
ScienceDex guides
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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.