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15,519 results for “r”
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>
R code for Snyder, Ellner, and Hooker, "Time and chance: using age partitioning to understand how luck drives variation in reproductive success"
<p>Over the course of individual lifetimes, luck usually explains a large fraction of the between- individual variation in lifespan or lifetime reproductive output (LRO) within a population, while variation in individual traits or "quality" explains much less. To understand how, where in the life cycle, and through which demographic processes luck trumps trait variation, we show how to partition by age the contributions of luck and trait variation to LRO variance, and how to quantify three distinct components of luck. We apply these tools to several empirical case studies.</p> <p>We find that luck swamps effects of trait variation at all ages, primarily due to randomness in individual state dynamics ("state trajectory luck"). Luck early in life is most important. Very early state trajectory luck generally determines whether or not an individual ever breeds, likely by ensuring that they are not dead or doomed quickly. Less early luck drives variation in success among those breeding at least once. Consequently, the importance of luck often has a sharp peak early in life, or two peaks. We suggest that ages/stages where the importance luck peaks are potential targets for interventions to benefit a population of concern, different from those identified by eigenvalue elasticity analysis.</p>
Two-step mixed model approach to analyzing differential alternative RNA splicing: Datasets and R scripts for analysis of alternative splicing
<p>Changes in gene expression can correlate with poor disease outcomes in two ways: through changes in relative transcript levels or through alternative RNA splicing leading to changes in relative abundance of individual transcript isoforms. The objective of this research is to develop new statistical methods in detecting and analyzing both differentially expressed and spliced isoforms, which appropriately account for the dependence between isoforms and multiple testing corrections for the multi-dimensional structure of at both the gene- and isoform- level. We developed a linear mixed effects model-based approach for analyzing the complex alternative RNA splicing regulation patterns detected by whole-transcriptome RNA-sequencing technologies. This approach thoroughly characterizes and differentiates three types of genes related to alternative RNA splicing events with distinct differential expression/splicing patterns. We applied the concept of appropriately controlling for the gene-level overall false discovery rate (OFDR) in this multi-dimensional alternative RNA splicing analysis utilizing a two-step hierarchical hypothesis testing framework. In the initial screening test we identify genes that have differentially expressed or spliced isoforms; in the subsequent confirmatory testing stage we examine only the isoforms for genes that have passed the screening tests. Comparisons with other methods through application to a whole transcriptome RNA-Seq study of adenoid cystic carcinoma and extensive simulation studies have demonstrated the advantages and improved performances of our method. Our proposed method appropriately controls the gene-level OFDR, maintains statistical power, and is flexible to incorporate advanced experimental designs.</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>
Census of R Coronae Borealis stars I: Infrared light curves from Palomar Gattini IR
<p>Lightcurves and spectra presented in the paper "Census of R Coronae Borealis stars I: Infrared light curves from Palomar Gattini IR", Karambelkar et al. 2021.</p>
Hybrids between Rubus idaeus and Rubus sect. Corylifolii and their relation to R. pruinosus and R. rosanthus
<p>We have studied hybrids between Rubus idaeus and various members of R. Sect. Corylifolii, primarily in Sweden. With the help of DNA-ploidy level determinations using flow cytometry and microsatellite DNA analysis of over 500 samples, we show that the material can be divided into four stable apomictic species (belonging to Subsect. Subidaei) and a large number of primary hybrids. Stable species can be recognised by a distribution that is distinct from the Corylifolii parent, a uniform morphology and an almost invariant genetic pattern. We confirm that R. cordatiformis has arisen from the hybrid R. eluxatus idaeus. Moreover, our study shows that R. lagerbergii has arisen from the hybrid R. dissimulans idaeus. For R. onsalaënsis, we unexpectedly identify the Corylifolii ancestor as a previously unidentified blackberry with a very restricted distribution in the northern part of the province of Halland, which is here described as R. antecedens. Furthermore, we show that R. pruinosus s. str. has arisen from the hybrid R. aureolus idaeus and that it is known only from a rather restricted area in the provinces of Småland, Östergötland and Södermanland in eastern Sweden. On the other hand, the great majority of what has been called R. pruinosus is a diverse collection of primary hybrids between R. idaeus and various Corylifolii species, which show a large variation both genetically and morphologically. The same applies to R. rosanthus, which represents R. norvegicus idaeus hybrids: The microsatellite analysis shows that they have arisen independently and therefore should be considered as primary hybrids. We have identified primary hybrids between R. idaeus and R. gothicus (by far the most common hybrid in Sweden), R. aureolus, R. camptostachys, R. decurrentispinus, R. eluxatus, R. friesianus, R. hallandicus, R. lidforssii and R. norvegicus.</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.
Pompeii - VI.6.1 Casa di Pansa - Latrine (R. 17)
The remains of this latrine were scanned as part of the 2022 Pompeii Water and Sanitation Project field school run by the University of Missouri. This is a textbook version of an ideal Pompeii style latrine, down a small hallway in the kitchen of the House of Pansa. A raised tile floor slopes down to a drain in the corner, while two pedestals would have functioned as supports for a wooden seat, now missing. The sloping floor would have allowed a bucket of water to be used to "flush" the contents of the latrine down the drain. More pictures of the latrine and of the house it's part of can be seen here: https://pompeiiinpictures.com/pompeiiinpictures/Fountains/Fountain%2080701.htm The model was generated in Agisoft Metashape from 250 photos taken using a Nikon Z5. Photo alignment was run on high, as was model generation - model has been decimated for export, and made manifold for 3D printing. Source: Objaverse 1.0 / Sketchfab
Nineveh North Palace, Room R Panel 28
Gypsum wall panel relief: return from the hunt. Men carry dead lions. Was on corridor leading to eastern gate out of the palace. The king probably passed this way on his way back from the hunt. This neo-Assyrian relief dates to 645 - 635 BC and was acquired by the British Museum in 1856. Length: 144.78 centimetres Width: 114.3 centimetres Source: Objaverse 1.0 / Sketchfab
Homage to a Starry Knight Since 1990 (R Cronk)
Scan of a "Homage to a Starry Knight Since 1990" in Venice Beach, CA. Taken with the Trnio Plus app using LiDar mode. Cleaned up in MeshMixer. https://www.westland.net/venice/art/cronk/starryknight.htm https://www.loc.gov/item/2013632394/ Source: Objaverse 1.0 / Sketchfab
Mare Street Baptist Chapel (MRH14_168_R)
A right patella from the Post-Medieval Mare Street Baptist Chapel excavations. This example exhibits a posterior compression fracture. Produced by Dr. Christian Steven Hoggard and Emma van der Velden (University of Southampton) for A Joint Effort (www.twitter.com/UoSJointEffort). Instagram: www.instagram.com/UoSJointEffort Data courtesy of Museum of London Archaeology (MOLA). Source: Objaverse 1.0 / Sketchfab
Replication Code in R for "Do Insurers Compete on the Federal Heath Insurance Exchange
<p>R code for univariate and multivariate analyses to model premiums based on the number of insurers in geographic rating areas.</p>
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>
Wrap your model in an R package!
<p>The groundwater drawdown model WTAQ-2, provided by the United States Geological Survey for free, has been "wrapped" into an R package, which contains functions for writing input files, executing the model engine and reading output files. By calling the functions from the R package a sensitivity analysis, calibration or validation requiring multiple model runs can be performed in an automated way. Automation by means of programming improves and simplifies the modelling process by ensuring that the WTAQ-2 wrapper generates consistent model input files, runs the model engine and reads the output files without requiring the user to cope with the technical details of the communication with the model engine. In addition the WTAQ-2 wrapper automatically adapts cross-dependent input parameters correctly in case one is changed by the user. This assures the formal correctness of the input file and minimises the effort for the user, who normally has to consider all cross-dependencies for each input file modification manually by consulting the model documentation. Consequently the focus can be shifted on retrieving and preparing the data needed by the model. Modelling is described in the form of version controlled R scripts so that its methodology becomes transparent and modifications (e.g. error fixing) trackable. The code can be run repeatedly and will always produce the same results given the same inputs. The implementation in the form of program code further yields the advantage of inherently documenting the methodology. This leads to reproducible results which should be the basis for smart decision making.</p>
Sequences, taxonomic assignments, and R script from Comparison of Lava Cave Bacterial Mat Communities to Overlying Surface Soil Bacterial Communities from Lava Beds National Monument, USA
<p>This set of files contain the 16S rDNA, taxonomic assignments from the greengenes database, and the R script for processing the data. </p> <p><strong>Abstract</strong></p> <p>Lava caves around the world often support extensive microbial mats on ceilings and walls in a range of colors. Little is known about lava cave microbial diversity and how these subsurface mats differ from microbial communities in overlying surface soils. We generated and analyzed bacterial 16S rDNA from 454 pyrosequencing from three colors of microbial mats (tan, white, and yellow) from seven lava caves in Lava Beds National Monument, CA, USA, and compared them with surface soils overlying each cave. <em>Actinobacteria</em> dominated in all samples, with 39% (caves) and 21% (surface soils). <em>Proteobacteria</em> made up 30% of phyla from caves and 36% from surface soil with <em>Gamma</em>- 20% and <em>Alpha</em>- 10% in the caves and <em>Gamma</em>- 18% with <em>Alpha</em>-17% in soil. Other major phyla in caves were <em>Nitrospirae</em> (7%) followed by Minor Phyla (7%), compared to surface soils with <em>Bacteriodetes</em> (8%) and Minor phyla (8%). A very high proportion (53.33%) of the most abundant sequences could not be identified to genus, indicating a high degree of novelty. Surface soil samples had more OTUs and greater diversity indices than cave samples. The same phyla were represented in both soils and cave microbial mats, but the overlap was only 11.2% at the operational taxonomic unit (OTU). Although surface soil microbes immigrate into underlying caves, the environment selects for microbes able to live in the cave habitats, resulting in very different cave microbial communities. In terms of species richness, diversity by mat color differed, but not significantly. Number of entrances per cave, distance from an entrance, cave length, and temperature also contributed to observed differences in diversity. With high levels of novel microbes, caves may represent excellent habitats for the isolation of new bioactive compounds. This study is the first comprehensive comparisons of bacterial communities in lava caves with the overlying soil community.</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>
Figure 8. - Metasternal process (in the circle) and aedeagi of Dicronocephalusadamsidrumonti and Dicronocephalusadamsiadamsi. A, B, C, D Dicronocephalusadamsidrumonti (Tibet) E, F, G, H Dicronocephalusadamsidrumonti (Sichuan) I, J, K, L Dicronocephalusadamsiadamsi (South Korea) M, N, O, P Dicronocephalusadamsiadamsi (North Korea) Q, R, S, T Dicronocephalusadamsiadamsi (Dandong, China).
Figure 8. - Metasternal process (in the circle) and aedeagi of Dicronocephalusadamsidrumonti and Dicronocephalusadamsiadamsi. A, B, C, D Dicronocephalusadamsidrumonti (Tibet) E, F, G, H Dicronocephalusadamsidrumonti (Sichuan) I, J, K, L Dicronocephalusadamsiadamsi (South Korea) M, N, O, P Dicronocephalusadamsiadamsi (North Korea) Q, R, S, T Dicronocephalusadamsiadamsi (Dandong, China).
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>
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.