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4,694 results for “data analysis”
Simulated data for "Spot-On: robust model-based analysis of single-particle tracking experiments"
<p><strong>Generation of simulated data</strong></p> <p>To systematically evaluate the performance of Spot-On as well as other common analysis tools such as MSD<sub>i</sub> and vbSPT, we considered a comprehensive set of 3480 realistic SPT simulations spanning the range of plausible dynamics. The simulations were performed using simSPT, which is freely available at GitLab: https://gitlab.com/tjian-darzacq-lab/simSPT. The simulation methods are described in detail at GitLab. A full description of the parameters which allows exact reproduction of the simulations is available together with the data (see Data Availability section). Briefly, we parameterized simSPT to consider that particles diffuse inside a sphere (the nucleus) of 8 µm diameter illuminated using HiLo illumination (assuming a HiLo beam width of 4 µm), with an axial detection range of ~700 nm, centered at the middle of the HiLo beam. Molecules are assumed to have a half-life of 4 frames (when inside the HiLo beam) and of 40 frames when outside the HiLo beam. The localization error was set to 25 nm and the simulation was run until 100000 in-focus trajectories were recorded. More specifically, the effect of the exposure time (1 ms, 4 ms, 7 ms, 13 ms, 20 ms), the free diffusion constant (from 0.5 µm²/s to 14.5 µm²/s in 0.5 µm²/s increments) and the fraction bound (from 0 % to 95 % in 5 % increments) were investigated, yielding a dataset consisting of 3480 simulations. The advantage of simulations is that the ground truth is known. This allows a quantitative assessment of which method works the best.</p> <p><strong>Content of the archives:</strong></p> <ol> <li>170718_simSPT_simulations.zip the code and instructions to reproduce the simulations</li> <li>4um.tar.bz2 simulated data inside a 4 µm nucleus</li> <li>20um.tar.bz2 simulated data inside a 20 µm nucleus, in which virtually no confinement occurs.</li> <li>subsampled.tar.bz2 is a set of subsampled datasets, containing either 99999, 30000, 10000, 3000, 1000, 300, 100 or 30 trajectories. Each subsampling was done 50 times, yielding 50 files per subsmpling.</li> </ol> <p><strong>Formats:</strong></p> <p>The data is provided both in CSV and .mat formats. .mat files are provided in the following dataset: 10.5281/zenodo.835541</p>
Supplementary data for ENACT: End-to-End Analysis and Cell Type Annotation for Visium High Definition (HD) Slides
<p>This project contains the datasets used to evaluate and reproduce the results of ENACT (End-to-End Analysis and Cell Type<br>Annotation for Visium HD Slides). The dataset consists of:</p> <ul> <li>a sample Visium HD sample of human colorectal cancer, courtesy of 10X Genomics (<a href="https://www.10xgenomics.com/datasets/visium-hd-cytassist-gene-expression-libraries-of-human-crc">Visium HD Spatial Gene Expression Library, Human Colorectal Cancer (FFPE) - 10x Genomics</a>). All credit goes to 10X Genomics.</li> <li>configuration files to be used to reproduce the results provided in the ENACT publication, </li> <li>evaluation plots used in the ENACT publication, and</li> <li>results obtained after running ENACT on the human colorectal cancer sample using the four bin-to-cell assignment methods (naive, weighted_by_area, weighted_by_transcript, and weighted_by_cluster) and the three cell annotation methods (Sargent, CellAssign, CellTypist)</li> </ul> <p>Additionally, results from running ENACT on the following three public VisiumHD samples are provided to showcase ENACT’s tissue-agnostic nature:</p> <div> <div> <div> <ul> <li> <p><a href="https://www.10xgenomics.com/datasets/visium-hd-cytassist-gene-expression-human-lung-cancer-post-xenium-expt">Human Lung FFPE</a> sample from a subject with Adenocarcinoma (age and gender unspecified),</p> </li> <li> <p><a href="https://www.10xgenomics.com/datasets/visium-hd-cytassist-gene-expression-human-tonsil-fresh-frozen">Human Tonsil Fresh Frozen</a> sample from a 21 year old male subject with Reactive Follicular Hyperplasia,</p> </li> <li> <p><a href="https://www.10xgenomics.com/datasets/visium-hd-cytassist-gene-expression-human-breast-cancer-fresh-frozen">Human Breast Fresh Frozen</a> sample from a 58 year old female subject with Ductal Carcinoma in Situ (DCIS).</p> </li> </ul> </div> </div> </div> <p> </p>
AnalyzAIRR: A user-friendly guided workflow for AIRR data analysis: example data and analysis source-code
<p>This repository contains:</p> <ul> <li>Annotated TCR-seq data files named <em>tripod-XX-XXXX</em></li> <li>The metadata corresponding to the annotated files</li> <li>The RepSeqExperiment object, which integrates the annotated files and the metadata and was used in the analysis pipeline</li> <li>The analysis script to generate the plots of the different figures</li> </ul>
Example Analysis Output of Xenium Breast Cancer Data
<p>This is an example CartoStore dataset from Xenium Breast Cancer Analysis.</p> <p>Outputs generated from XeniumRanger and FICTURE are combined in this repository. </p> <p>Please refer to https://github.com/seqscope/cartloader for more details. </p>
Matlab codes implementing the XDROM+ data-driven ENSO forecast model and some analysis of it
<p>This is the BEST forecast model of large scale features of ENSO as of today, beating (Zhao et al. Nature 2024).</p> <p>This archive is supplementary to a comment article concerning (Zhao et al. Nature 2024) intended as a "Matters Arising" piece to be submitted to Nature (https://www.researchsquare.com/article/rs-5336072/v1). Given that i criticise also the handling editor and 3 reviewers of (Zhao et al. Nature 2024) calling their incompetence out, do not be surprised if you have to look for the paper in some other journal instead. Oh well, integrity is above all else, no?! On that note, may I interest you in a bit of sci-fi? https://www.linkedin.com/pulse/crime-punishment-bit-differently-tamas-bodai-g4cvf/?trackingId=WdQkSNjgSuyxlyWVLRonrw%3D%3D</p>
Supplementary materials for "Putting the F into FBD analysis: tree constraints or morphological data ?"
<p>This dataset contains the R code, simulated datasets and configuration files used to run the analyses presented in the manuscript "Putting the F into FBD analysis: tree constraints or morphological data ?".</p>
Data from: Pan-genome analysis highlights the role of structural variation in the evolution and environmental adaptation of Asian honeybees
<p>The <em>Asian honeybee</em>, <em>Apis cerana</em>, is an ecologically and economically important pollinator. Mapping its genetic variation is key to understanding population-level health, histories, and potential capacities to respond to environmental changes. However, most efforts to date were focused on single nucleotide polymorphisms (SNPs) based on a single reference genome, thereby ignoring larger-scale genomic variation. We employed long-read sequencing technologies to generate a chromosome-scale reference genome for the ancestral group of<em> A. cerana</em>. Integrating this with 525 resequencing datasets, we constructed the first pan-genome of <em>A. cerana</em>, encompassing almost the entire gene content. We found that 31.32% of genes in the pan-genome were variably present across populations, providing a broad gene pool for environmental adaptation. We identified and characterized structural variations (SVs) and found that they were not closely linked with SNP distributions, however, the formation of SVs was closely associated with transposable elements. Furthermore, phylogenetic analysis using SVs revealed a novel <em>A. cerana</em> ecological group not recoverable from the SNP data. Performing environmental association analysis identified a total of 44 SVs likely to be associated with environmental adaptation. Verification and analysis of one of these, a 330 bp deletion in the Atpalpha gene, indicated that this SV may promote the cold adaptation of <em>A. cerana</em> by altering gene expression. Taken together, our study demonstrates the feasibility and utility of applying pan-genome approaches to map and explore genetic feature variations of honeybee populations, and in particular to examine the role of SVs in the evolution and environmental adaptation of <em>A. cerana</em>.</p>
Data from "FICTURE: Scalable segmentation-free analysis of sub-micron resolution spatial transcriptomics"
Open the record for dataset details and reuse information.
Statistical Analysis of Overlapping Double Ion Energy Dispersion Events in the Northern Cusp (Paper Data and Code)
<p>This data and code accompanies the paper <i>Statistical Analysis of Overlapping Double Ion Energy Dispersion Events in the Northern Cusp</i>, published in Frontiers in Astronomy and Space Sciences in 2023. This upload includes a CSV list of the selected events, a human-readable table of the selected events (see below), plots of each selected event, and the code used to select the events.</p><p>The code in this repository is a fork of <a href="https://github.com/ddasilva/dmsp-dispersion-detection">https://github.com/ddasilva/dmsp-dispersion-detection</a> at the time of publication. Future updates may exist on GitHub.</p><p><br> </p>
Input data for boreal tip analysis code
<p>Input data for analysis code of boreal tip repository.<br>Includes central European geographical subsets of CRU TS, MOD44B, GLC2000, MPI-ESM and CHELSA-TraCE21k data products as well as paths for download of complete data sets.</p>
Data from Nicolle et al. LC-HRMS study of Streptomyces sp. AgN23 Culture Media Extract. Study of AgN23 exometabolome and analysis of Arabidopsis metabolomic responses to the bacteria
<p>This archive compiles several datasets related to studies of <i>Streptomyces</i> sp. AgN23 interaction with <i>Arabidopsis thaliana</i>. Ultra-high-performance liquid chromatography-high-resolution MS (UHPLC-HRMS) analyses were performed on a Q Exactive Plus quadrupole (Orbitrap) mass spectrometer, equipped with a heated electrospray probe (HESI II) coupled to a U-HPLC Ultimate 3000 RSLC system (Thermo Fisher Scientific, Hemel Hempstead, United Kigdom). For each biological sample, the RAW file obtained in ESI+ and ESI- mode were retrieved from the Xcalibur version 4.4 software and are deposited in separate sub-folders termed "RawPos" and "RawNeg". Each experimental cohort is grouped in a folder where the biological repeats can be retrieved, as well as QC (Quality Check, pool of all samples from the cohort), Blank samples and eventual alternative control such as Bennett, the mock control media of <i>Streptomyces</i> sp. AgN23. The details regarding samples preparation, analytic parameters and mass spectrometry, statistical treatment and visualization of the data will be made available in the publication relating to this archive. The folder " AgN23-WT_AgN23-pSC004" contains chromatograms related to metabolomic study of Wild-type and pSC004-1, pSC004-10, pSC004-16 and pSC004-22 mutants of <i>Streptomyces</i> sp. AgN23. The folder " Col-0_AgN23" contains chromatograms related to metabolomic study of <i>Arabidopsis thaliana</i> Col-0 responses to colonization by <i>Streptomyces</i> sp. AgN23-WT. The folder " Col-0_pad3-1_AgN23" contains chromatograms related to metabolomic study of <i>Arabidopsis thaliana</i> Col-0 and the <i>Arabidopsis</i> pad3-1 mutant responses to colonization by <i>Streptomyces</i> sp. AgN23-WT. The folder " Col-0_pSC004" contains chromatograms related to metabolomic study of <i>Arabidopsis thaliana</i> Col-0 responses to colonization by <i>Streptomyces</i> sp. AgN23-WT and the AgN23 mutants pSC004-10 and pSC004-22. It should be noted that in the publication associated with this archive, the pSC004-1, pSC004-10, pSC004-16 and pSC004-22 mutants are referred to as ΔgbnB-1, ΔgbnB-2, ΔgbnB-3 and ΔgbnB-4, respectively.</p>
Data for: The Clam Before the Storm: A Meta Analysis Showing the Effect of Combined Climate Change Stressors on Bivalves
<p>These data were used to conduct a meta-analysis (as descirbed in the pre-print; The Clam Before the Storm: A Meta Analysis Showing the Effect of Combined Climate Change Stressors on Bivalves). These data can be used to reproduce our analysis.</p>
Data for geometric analysis of seed shape diversity in the Cucurbitaceae
<p>Data to complement the article Geometric analysis of seed shape diversity in the Cucurbitaceae </p>
Reception of a physical activity intervention program in German older adults. Data from a feedback analysis of PROMOTE II.
<p>As part of the<strong> AEQUIPA </strong>prevention research network, the aim of the <strong>PROMOTE II</strong> study was to gain insights into primary prevention for healthy aging. One focus was on the development and dissemination of ready-to-use tools and work aids to promote physical activity.</p><p>As part of a nine-month randomized trial with a cross-over design among adults aged 60 and above, eligible participants from 14 districts in Bremen in proximity to the two study centers (one in the North and one in the East of the city of Bremen, Germany) were randomly assigned to either a) a print-based intervention (PRINT) or b) a web-based intervention (WEB). Randomly selected thirty percent of the web-based intervention group received an activity tracker in addition (WEB+).</p><p>Usage of program components, attendance of group sessions and acceptance of the intervention were assessed via self-administered paper-based questionnaires three and nine months after baseline as well as feedback interviews and class recordings. Participant feedback was analyzed using quantitative methods on a descriptive basis, as well as using qualitative content analysis of open-ended questions, group-interviews and protocols based on the socio-ecological model as coding framework.</p><p>This publication provides the coding matrix, including the participant feedback data.</p>
Surface Strain Data and Principal Component Analysis from Crystal Plasticity Simulations
<p>This is a dataset of surface strain data along y-z surfaces during tensile loading along the x direction of polycrystalline Al samples. Surface strain data are recorded during periodic intervals. Principal component analysis is implemented on the loading sequences.</p>
Data and analysis scripts: Evidence supporting an evolutionary trade-off between material properties and architectural design in Anolis lizard long bones
<p>In biology, 'many-to-one mapping' occurs when multiple morphological forms can meet a particular functional demand. Knowledge of this mapping is crucial for understanding how selection on performance shapes the evolution of morphological diversity. Past research has focused primarily on the potential for geometrically alternative morphological designs to produce equivalent performance outcomes. Here we ask whether the material properties of biological tissues hold similar potential. Through phylogenetic comparative study of <em>Anolis</em> lizards, we show that the architectural design and mineral density of the femur trade off in a many-to-one functional system, yielding a morphospace featuring parallel isolines in size-relative bending strength. Anole femur evolution has largely tracked a narrow band of strength isolines over phylogenetic timescales, suggesting that geometry and mineral content shape the course of macroevolution through compensatory effects on performance. Despite this conserved evolutionary relationship, insular and continental species evolve strong bones differently, likely reflecting underlying ecological differences. Mainland anoles, which exhibit fast-paced life histories, typically have femora with lower mineralization and thinner walls than island species, which exhibit the opposite strategy. Together, our results reveal an overlooked dimension in the relationship between form and function, expanding our understanding of how many-to-one mapping can shape patterns of phenotypic diversity.</p>
Automated bio-AFM generation of large mechanome data set and their analysis by machine learning to classify prostatic cell lines_Training base 100 PC3-GFP
Open the record for dataset details and reuse information.
Data and code from Lamb et al., "Evaluating conservation units using network analysis: a sea duck case study"
<p>This file consists of data and code used to construct network models for scoters in North America and is associated with the manuscript "<strong>Evaluating conservation units using network analysis: a sea duck case study</strong>" published in Frontiers in Ecology and the Environment. </p><p> </p><p><strong>Continental scoter network mapping </strong>is the R script used to run analyses.</p><p> </p><p><strong>duck_nodes</strong> is the main datafile. Columns are organized as follows:</p><p>id - unique identifier</p><p>species - species from which the centroid was obtained (BLSC = black scoter, SUSC = surf scoter, WWSC = white-winged scoter)</p><p>stage - period of the annual cycle to which the centroid belongs (W = winter, B = breeding, S = spring staging, M = fall staging and molt, WM = winter migration, BM = breeding migration, MM = molt migration, SM = spring migration)</p><p>site - position of centroid within season (i.e., W1 = first site occupied during winter, W2 = second site occupied, etc.)</p><p>cycle - number of annual cycles following transmitter attachment (1 = first cycle after attachment, 2 = second cycle after attachment, etc.)</p><p>sex - sex of individual (M = male, F = female)</p><p>age - age of individual (HY = hatch year, SY = second year, TY = third year, ASY = after second year, ATY = after third year, AHY = after hatch year</p><p>capture_reg - general area where individual was captured</p><p>capture_subreg - specific region within capture region where individual was captured</p><p>lon - longitude of centroid</p><p>lat - latitude of centroid</p><p>duration - number of days spent at centroid</p><p>start - date of arrival at centroid</p><p>end - date of departure from centroid</p><p>jstart - Julian date of arrival at centroid</p><p>jend - Julian date of departure from centroid</p><p>season - season of annual cycle in which centroid occurred (W = winter, F = fall, B = breeding, S = spring)</p><p>year - calendar year in which centroid began</p><p>to - node in which centroid is grouped</p><p>from - node in which previous centroid is grouped (i.e., node in which indiviual was located before moving to present node)</p><p>to_sea - season of annual cycle in which centroid occurred</p><p>from_sea - season of annual cycle in which previous centroid occurred</p><p>type - movement type to centroid; the first letter represents the season (coded as in "season" column), and the second represents the nature of the movement (WD = dispersal within a season, M = migration among seasons)</p><p>type2 - same as "type", but with dispersal movements coded by the stage in which they occur (W = winter, B = breeding, SM = spring migration, WM = winter migration)</p><p>ew - capture location in eastern (east; Atlantic and Great Lakes) or western (west; Pacific) North America</p><p>count_ind_sp - total number of tracked individuals of the species represented by centroid</p><p>wt - base centroid weight (all centroids equal, deployments excluded)</p><p>wt_sp - species-adjusted centroid weight: for centroid <i>x</i> in species <i>s</i>, weight<i>x</i> = (<i>N </i>centroids) × (1 / (<i>n </i>centroids in <i>s</i>))</p><p>wt_dur - duration-adjusted centroid weight: for centroid <i>x</i>, weight<i>x</i> = (days at centroid location) × 365-1</p><p>wt_ind - individual-adjusted centroid weight: for centroid <i>x</i> in individual<i> j</i>, weight<i>x</i> = 1 / (<i>n </i>centroids in <i>j</i>)</p><p>wt_ind_sp - individual and species adjusted centroid weight: for centroid <i>x</i>, individual <i>j</i>, and species <i>s</i>, weight<i>x</i> = (<i>N </i>centroids / (<i>N </i>species * <i>n</i> individuals in <i>s</i>)) × (1 / (<i>n </i>centroids in <i>j</i>))</p><p>wt_cap - capture location adjusted centroid weight: for centroid <i>x</i> and capture location <i>c, </i>weight<i>x </i>= (<i>N </i>centroids / <i>N</i> capture locations) / <i>n</i> centroids in <i>c</i></p><p>wt_ew - east-west adjusted centroid weight: for for centroid <i>x</i> and region <i>r, </i>weight<i>x </i>= (<i>N </i>centroids / <i>N</i> regions) / <i>n</i> centroids in <i>r</i></p><p>wt_spew - species and east-west adjusted centroid weight: for centroid <i>x</i> species <i>s</i>, and region <i>r, </i>weight<i>x </i>= (<i>N </i>centroids / (<i>N</i> species × <i>N</i> regions)) / <i>n </i>centroids for species <i>s</i> in region <i>r</i></p><p>wt_indspew - individual, species, and east-west adjusted centroid weight: for centroid <i>x,</i> individual<i> j, </i>species <i>s</i>, and region <i>r, </i>weight<i>x </i>= <i>N </i>centroids / (<i>N</i> species × <i>N</i> regions × <i>n</i> centroids for individual <i>j </i>× <i>n</i> individuals for species <i>s</i> in region <i>r</i>)</p><p>wt_spewcap - species, east-west, and capture location adjusted centroid weight: for centroid <i>x,</i> species <i>s</i>, capture location <i>c, </i>and region <i>r, </i>weight<i>x </i>= <i>N </i>centroids / (<i>N</i> species × <i>N</i> regions × <i>n</i> centroids for species <i>s</i> in capture location <i>c </i>× <i>n</i> capture locations for species <i>s</i> in region <i>r</i>)</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>
Data for: The meta-analysis of the effects of spatial sampling bias correction on presence only species distribution models
<p>This dataset contains information extracted from 70 studies identified through a systematic review of the peer-reviewed literature (Web of Science and SCOPUS databases both searched on the 13/02/2023) to evaluate the effect of spatial sampling bias correction methods in presence-only species distribution models.</p>
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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.