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1,249 results for “R data”
Orthographic and phonological processing in Hong Kong deaf readers: Data and R Scripts
<p>This data was reported on in an article titled "Orthographic and phonological processing in Hong Kong deaf readers: An eye-tracking study."</p>
Spectral data and R modeling code from: Polarized light sensitivity in Pieris rapae is dependent on both color and intensity
<p>This dataset provides supplementary spectral data and the R code underlying the spectral sensitivy moding of female <em>Pieris rapae</em> photoreceptors used in the manuscript "Polarized light sensitivity in <em>Pieris rapae</em> is dependent on both color and intensity".</p>
Evidence for an extreme founding effect in a highly successful invasive species: data and R code
<p>The adaptive potential of invasive species is thought to decrease during founding events due to reduced genetic diversity, limiting the new population's ability to colonize novel habitats. Barbary ground squirrels (<i>Atlantoxerus getulus</i>) were purportedly introduced as a single breeding pair to the island of Fuerteventura but have expanded to over a million individuals spread across the island in just over 50 years. We estimated the number of founders and measured the level of genetic diversity in this population using the mitochondrial displacement loop and microsatellite markers. Island samples (<i>n</i> = 19) showed no variation in the d-loop, suggesting a single founding female, while Moroccan samples (<i>n</i> = 6) each had unique mitochondrial haplotypes. The microsatellite data of the island population (<i>n</i> = 256 individuals) revealed a small effective population size, low levels of heterozygosity, and high levels of inbreeding, supporting a founding population size of two to three individuals. Our results suggest that <i>A. getulus</i> has undergone an intense genetic bottleneck during their colonization of the island. They are one of the few species where introduction effort does not explain invasion success, although further investigation may explain how they have avoided the worst expected effects following an extreme genetic bottleneck.</p>
Data & R Scripts - Short and long-term effects of low-sulphur fuels on marine zooplankton communities
<p>Data and R scripts associated with "Short and long-term effects of low-sulphur fuels on marine zooplankton communities" https://doi.org/10.1016/j.aquatox.2020.105592 </p>
Learning can be detrimental for a parasitic wasp: R scripts and Telenomus podisi data
<p>Animals have evolved the capacity to learn, and the conventional view is that learning allows individuals to improve foraging decisions. We describe a first case of maladaptive learning where a parasitoid learns to associate chemical cues from an unsuitable host, thereby re-enforcing a reproductive cul-de-sac (evolutionary trap). <i>Telenomus podisi</i> parasitizes eggs of the exotic stink bug <i>Halyomorpha halys</i> at the same rate as eggs of its coevolved host, <i>Podisus maculiventris</i>, but the parasitoid cannot complete its development in the exotic species. We hypothesized that <i>T. podisi </i>learns to exploit cues from this non-coevolved species, thereby increasing unsuccessful parasitism rates. We conducted bioassays to compare the responses of naïve <i>vs</i>. experienced parasitoids on chemical footprints left by one of the two host species. Both naïve and experienced females showed a higher response to footprints of <i>P. maculiventris</i> than of <i>H. halys</i>. Furthermore, parasitoids that gained an experience on <i>H. halys</i> significantly increased their residence time within the arena and the frequency of re-encounter with the area contaminated by chemical cues. Maladaptive learning in the <i>T. podisi</i> - <i>H. halys</i> association is expected to further decrease parasitoid reproductive success and have consequences for population dynamics of sympatric native and exotic host species.</p>
Data and R code for The Finer Points of Urban Adaptation: Intraspecific Variation in Lizard Claw Morphology (2020; Biological Journal of the Linnean Society)
<p>This zip file contains all data (tps files, Rdata, csv) and annotated R script to conduct all analyses presented in Falvey et al. (2020, BJLS), which examines claw morphology in 5 species of anole lizards using geometric morphometrics.</p>
Supplementary files for Crane et al., "Lots of movement, little progress": R Code, data and figures
<p>Datasets, R code and figures pertaining to the manuscript: Crane M, Silva I, Marshall BM, & Strine CT.<em> Lots of movement, little progress: A review of reptile home range literature.</em></p>
Data and R code from: Modelling the evolution of cognitive styles
Background <p>Individuals consistently differ in behaviour, exhibiting so-called personalities. In many species, individuals differ also in their cognitive abilities. When personalities and cognitive abilities occur in distinct combinations, they can be described as 'cognitive styles'. Both empirical and theoretical investigations produced contradicting or mixed results regarding the complex interplay between cognitive styles and environmental conditions.</p> Results <p>Here we use individual-based simulations to show that, under just slightly different environmental conditions, different cognitive styles exist and under a variety of conditions, can also co-exist. Co-existences are based on individual specialization on different resources, or, more generally speaking, on individuals adopting different niches or microhabitats.</p> Conclusions <p>The results presented here suggest that in many species, individuals of the same population may adopt different cognitive styles. Thereby the present study may help to explain the variety of styles described in previous studies and why different, sometimes contradicting, results have been found under similar conditions.</p>
Data from: nlstimedist: an R package for the biologically meaningful quantification of unimodal phenology distributions
Phenological investigation can provide valuable insights into the ecological effects of climate change. Appropriate modelling of the time distribution of phenological events is key to determining the nature of any changes, as well as the driving mechanisms behind those changes. Here we present the nlstimedist R package, a distribution function and modelling framework that describes the temporal dynamics of unimodal phenological events. The distribution function is derived from first principles and generates three biologically interpretable parameters. Using seed germination at different temperatures as an example, we show how the influence of environmental factors on a phenological process can be determined from the quantitative model parameters. The value of this model is its ability to represent various unimodal temporal processes statistically. The three intuitively meaningful parameters of the model can make useful comparisons between different time periods, geographical locations or species' populations, in turn allowing exploration of possible causes.
Data from: An R package and online resource for macroevolutionary studies using the ray-finned fish tree of life
1. Comprehensive, time-scaled phylogenies provide a critical resource for many questions in ecology, evolution, and biodiversity. Methodological advances have increased the breadth of taxonomic coverage in phylogenetic data; however, accessing and reusing these data remain challenging. 2. We introduce the Fish Tree of Life website and associated R package fishtree to provide convenient access to sequences, phylogenies, fossil calibrations, and diversification rate estimates for the most diverse group of vertebrate organisms, the ray-finned fishes. The Fish Tree of Life website presents subsets and visual summaries of phylogenetic and comparative data, and is complemented by the R package, which provides flexible programmatic access to the same underlying data source for advanced users wishing to extend or reanalyze the data. 3. We demonstrate functionality with an overview of the website, and show three examples of advanced usage through the R package. First, we test for the presence of long branch attraction artifacts across the fish tree of life. The second example examines the effects of habitat on diversification rate in the pufferfishes. The final example demonstrates how a community phylogenetic analysis could be conducted with the package. 4. This resource makes a large comparative vertebrate dataset easily accessible via the website, while the R package enables the rapid reuse and reproducibility of research results via its ability to easily integrate with other R packages and software for molecular biology and comparative methods.
Supplementary Material for Frontiers Plant Genetics and Genomics 'Novel R tools for analysis of genome-wide population genetic data with emphasis on clonality'
<p>Authors</p> <p>Zhian N. Kamvar, Jonah C. Brooks, and Niklaus J. Grünwald</p>
R data set: The Cancer Genome Atlas Gene Expression data
<p>This compound data set comprises the following information from the The Cancer Genome Atlas:</p> <ul> <li>RNA-Seq counts for 60483 genes across 11093 samples</li> <li>HuEx 1.0 ST gene expression data for 18632 genes across 1211 samples</li> <li>clinical indicators for 11160 patients</li> </ul> <p>All gene expression data is annotated across ENSEMBL, ENTREZ and symbols. Samples are annotated by TCGA barcodes.</p> <p>To read the data set into R (requires 6 GB of RAM) use:</p> <p>tcga <- readRDS("tcga.rds")</p>
Database including meta data and R script for bachelor thesis biology on ground beetles as bioindicator 2017
<p>Database including meta data and R script for bachelor thesis biology on ground beetles as bioindicator 2017</p>
Data and R code used in Alonso-Crespo et al (2024) Exploring priority and year effects on plant diversity, productivity and vertical root distribution: first insights from a grassland field experiment
<p>This release contains the raw data, R code, and RootPainter model supporting the results described in Alonso-Crespo et al (2024) Exploring priority and year effects on plant diversity, productivity and vertical root distribution: first insights from a grassland field experiment.</p>
RecView: An interactive R application for locating recombination positions using pedigree data
<p><span>We present <em>RecView</em>, an interactive R application and </span><span>its homonymous R package</span><span>, to facilitate locating recombination positions along chromosomes or scaffolds using whole-genome genotype data of a three-generation pedigree. </span><span>We demonstrate applicability of <em>RecView </em>using the genotype data from two offspring, as well as their grandparents and parents, of the great reed warbler (<em>Acrocephalus arundinaceus</em>).</span></p>
Data and R analysis code: Asian elephants distinguish sexual status and identity of unfamiliar elephants using urinary odours
<p class="MsoNormal"><span>Despite the ubiquity of odours in mammals, few studies have documented the natural olfactory abilities of many "non-model" species such as the Asian elephant. As Asian elephants are endangered, we may apply odours to more effectively manage threatened populations. We implemented a habituation–discrimination paradigm for the first time in Asian elephants to test the ability of elephants to discriminate between unfamiliar male elephant urine, hypothesizing that elephants would successfully distinguish non-musth from musth urine and also distinguish identity between two closely related individuals. We conducted two bioassay series, exposing three female and three male zoo-housed elephants to the same urine sample (non-musth urine in the first series, and urine from an unfamiliar individual in the second) over five days. On the sixth day, we simultaneously presented each elephant with a novel sample (either musth urine or urine from a second unfamiliar individual) alongside the habituated urine sample, comparing rates of chemosensory response to each sample to indicate discrimination. All elephants successfully discriminated non-musth from musth urine, and also urine from two unfamiliar half-brothers. Our results further demonstrate the remarkable olfactory abilities of elephants with promising implications for conservation and management.</span></p>
Raw data and R code for statistical analyses from: Sensory trap leads to reliable communication without a shift in nonsexual responses to the model cue
<p>The sensory trap model of signal evolution suggests that males manipulate females into mating using traits that mimic cues used in a nonsexual context. Despite much empirical support for sensory traps, little is known about how females evolve in response to these deceptive signals. Female sea lamprey (<em>Petromyzon marinus</em>) evolved to discriminate a male sex pheromone from the larval odor it mimics and orient only towards males during mate search. Larvae and males release the attractant 3-keto petromyzonol sulfate (3kPZS), but spawning females avoid larval odor using the pheromone antagonist, petromyzonol sulfate (PZS), which larvae but not males, release at higher rates than 3kPZS. We tested the hypothesis that migratory females also discriminate between larval odor and the male pheromone and orient only to larval odor during anadromous migration, when they navigate within spawning streams using larval odor before they begin mate search. In-stream behavioral assays revealed that, unlike spawning females, migratory females do not discriminate between mixtures of 3kPZS and PZS applied at ratios typical of larval versus male odorants. Our results indicate females discriminate between the sexual and nonsexual sources of 3kPZS during but not outside of mating and show sensory traps can lead to reliable sexual communication without females shifting their responses in the original context.</p>
Harmonized data and R code for "Coherent response of zoo- and phytoplankton assemblages to global warming since the Last Glacial Maximum"
<p>Harmonized data and R code for "<em>Coherent response of zoo- and phytoplankton assemblages to global warming since the Last Glacial Maximum</em>"<br>by Tonke Strack, Lukas Jonkers, Marina C. Rillo, Karl-Heinz Baumann, Helmut Hillebrand and Michal Kucera (submitted to <em>Global Ecology and Biogeography</em>, 2024).</p> <p><strong>STRUCTURED ABSTRACT</strong><br><em>Aim</em>: We use the fossil record of different marine plankton groups to determine how their biodiversity changed during past climate warming comparable to projected future warming.<br><em>Location</em>: North Atlantic Ocean and adjacent seas. Time series cover a latitudinal range of 75°N to 6°S.<br>Time period: Past 24,000 years, i.e., from the Last Glacial Maximum (LGM) to the current warm period covering the last deglaciation.<br><em>Major taxa studied</em>: Planktonic foraminifera, dinoflagellates and coccolithophores.<br><em>Methods</em>: We analyse time series of fossil plankton communities using principal component analysis and generalised additive models to estimate the overall trend of temporal compositional change in each plankton group and identify periods of significant change. We further analyse local biodiversity change by analysing species richness, species gains and losses, and the effective number of species in each sample and compare alpha diversity to the LGM mean.<br><em>Results</em>: All plankton groups show remarkably similar trends in the rates and spatio-temporal dynamics of local biodiversity change and a pronounced non-linearity with climate change in the current warm period. Assemblages of planktonic foraminifera and dinoflagellates started to significantly change with the onset of global warming around 15,500 to 17,000 years ago and continued to change at the same pace during the current warm period until at least 5,000 years ago, while coccolithophores assemblages changed at a constant rate throughout the past 24,000 years seemingly irrespective of the prevailing temperature change.<br><em>Main conclusions</em>: The climate change during the transition from the LGM to the current warm period led to a long-lasting reshuffling of the zoo- and phytoplankton assemblages likely associated with the emergence of new ecological interactions and possibly a shift in the dominant drivers of plankton assemblage change from more abiotic-dominated causes during the last deglaciation to more biotic-dominated causes with the onset of the Holocene.</p> <p><strong>CONTENT</strong><br>This dataset includes the harmonized assemblage data of the three investigated plankton groups (planktonic foraminifera, dinoflagellates and coccolithophores) as well as all the R code needed to re-produce the results of this study and it's main figures.</p> <p>Scripts written by Tonke Strack</p> <p><br><strong>DATA SOURCES</strong><br>1) GMST: Osman, M. B. et al. Globally resolved surface temperatures since the Last Glacial Maximum. <br> <em>Nature</em> 599, 239-244, doi:10.1038/s41586-021-03984-4 (2021).<br>2) WOA18: Locarnini, R. A. et al. World Ocean Atlas 2018, Volume 1: Temperature. A. Mishonov, <em>Technical Editor. </em><br><em> NOAA Atlas NESDIS</em> 81, 52 (2019).<br>3) plankton assemblage data: individual data references provided in CoreList.csv</p> <p><br><strong>DATA</strong><br>1. Harmonized assemblage data<strong>*</strong>: <em>FullDataTable_PF_harmonized.txt</em><br>2. Core list of additional information on time series: <em>CoreList.csv</em><br>3. Reference lists for species names names: <em>ReferenceList_PlanktonicForaminifera.csv, ReferenceList_Dino.csv, ReferenceList_Cocco.csv</em></p> <p><br><strong>CODE</strong><br>1. <em>01_LoadData.R</em>: loads harmonized assemblage data from planktonic foraminifera, dinocyst and coccolithophores<br>2. <em>02_GMST_import.R</em>: loads loads the globally resolved surface temperature since the LGM from Osman et al. (2011)<br>3. <em>03_DataAnalysis_PCA_GAM.R</em>: PCA/GAM analysis on the plankton assemblage data (results shown in Figure 2 and 3), sensititvity analysis (results shown in Figure 4), and some summary statistics<br>4. <em>04_DataAnalysis_MH_GAM_AlternativeApproach.R</em>: alternative GAM approach using Morisita-Horn index (results shown in Figure S2, S3 and S4)<br>5. <em>05_DataAnalysis_BiodiversityChange.R</em>: local biodiversity change analysis of individual time series (results shown in Figure 5, 6 and S9)</p> <p><br>*Assemblage data of individual time series were manually downloaded, quality checked, taxonomically harmonized, and combined into one data file.<br>Planktonic foraminifera data were harmonized following Siccha and Kuchera (2017). We merged <em>Globigerinoides ruber ruber</em> and <em>Globigerinoides ruber </em><br><em>albus</em>, because some studies only reported them together as<em> Globigerinoides ruber</em>. Also, P/D intergrades (an informal category of morphological<br>intermediates between <em>Neogloboquadrina incompta</em> and <em>Neogloboquadrina dutertrei</em>) were merged with <em>Neogloboquadrina incompta</em>.<br>Dinocyst taxonomy was harmonized following de Vernal et al. (2020) with slight additions following Zonneveld et al. (2013). Names that could not be<br>resolved using synonym lists and assigned a harmonized name following de Vernal et al. (2020) and Zonneveld et al. (2013) were treated as unidentified<br>specimens and were excluded from the assemblage analyses. These specimens were present in 4 time series and were rare taxa (relative abundances < 3%).<br>The protoperidinoids were also excluded from further assemblage analyses as this category includes all unidentified brownish cysts (de Vernal et al., 2020).<br>Coccolithophore taxonomy follows Young et al. (2003) and coccolith countings were conducted on a scanning-electron microscope (SEM) to ensure that all<br>specimens are resolved to the species level. We merged <em>Coccolithus pelagicus</em> subspecies, because they were not distinguished in all studies. <br>Species not reported in the time series data were assumed to be absent (that is, zero abundance) which is in accordance with the completeness of the counts<br>reported in the original studies. The original data were either given in absolute or relative abundances, and after excluding unnecessary columns<br>(unidentified or rare taxa that could not be harmonised) the abundances were recalculated to 100 %. In total, 41 species of planktonic foraminifera,<br>30 species of coccolithophores and 53 species of organic-walled dinocysts were observed in our study.</p> <p><strong>REFERENCES</strong><br>de Vernal, A., Radi, T., Zaragosi, S., Van Nieuwenhove, N., Rochon, A., Allan, E., . . . Richerol, T. (2020). Distribution of common modern dinoflagellate cyst taxa in surface sediments of the Northern Hemisphere in relation to environmental parameters: The new n=1968 database. <em>Mar. Micropaleontol.</em>, 159. doi:10.1016/j.marmicro.2019.101796<br>Siccha, M. & Kucera, M. ForCenS, a curated database of planktonic foraminifera census counts in marine surface sediment samples. S<em>ci. Data</em> 4, 170109, doi:10.1038/sdata.2017.109 (2017).<br>Young, J. R., Geisen, M., Cros, L., Kleijne, A., Sprengel, C., Probert, I., & Østergaard, J. B. (2003). A guide to extant coccolithophore taxonomy. <em>Journal of Nannoplankton Research Special Issue</em>, 1, 1-125. doi:10.58998/jnr2297<br>Zonneveld, K. A. F., Marret, F., Versteegh, G. J. M., Bogus, K., Bonnet, S., Bouimetarhan, I., . . . Young, M. (2013). Atlas of modern dinoflagellate cyst distribution based on 2405 data points. <em>Rev. Palaeobot. Palynol.</em>, 191, 1-197. doi:10.1016/j.revpalbo.2012.08.003</p>
R-XIMO experiment data
<p>The data utilized in the R-XIMO article:</p> <p>Misitano, G., Afsar, B., Lárraga, G. <em>et al.</em> Towards explainable interactive multiobjective optimization: R-XIMO. <em>Auton Agent Multi-Agent Syst</em> <strong>36</strong>, 43 (2022). https://doi.org/10.1007/s10458-022-09577-3</p> <p>Re-uploaded to Zenodo because the original link in the article does not work anymore.</p>
Data and R code for machine learning modelling of favourite places and routes of outdoor recreation
<p>This is a script showing the analysis used in a paper submitted for review in Landscape and Urban Planning, titled "Seeing through their eyes: Revealing recreationists’ landscape preferences through viewshed analysis and machine learning", by Carl Lehto, Marcus Hedblom, Anna Filyushkina and Thomas Ranius. </p> <p>The zip file contains an R script, data saved in .rds format and a R workspace. </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.