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764 results for “Reproducible”
Genotype reproducibility testing in next-generation sequencing data
<p>Code, log and results summary for testing the reproducibility of genotypes with three pairs of hemiclones in the Sussex LH<sub>M </sub><em>D.melanogaster </em>population sample. Discovery and genotyping of genomic sequence variants was done using GATK HaplotypeCaller, and Genomestrip. Numerical comparison of genotype calls within each pairs of hemiclone individuals was performed using GATK GenotypeConcordance.</p> <p> </p> <p>The pre-print manuscript for this data is available on biorxiv: "Whole genome resequencing of a laboratory-adapted Drosophila melanogaster population sample" http://biorxiv.org/content/early/2016/10/17/081554 doi: http://dx.doi.org/10.1101/081554</p>
[J.D. Hooker s.n., CAL] [© Botanical Survey of India, Central National Herbarium. Reproduced with permission] in Lectotypification of Arisaema consanguineum Schott (Araceae)
[J.D. Hooker s.n., CAL] [© Botanical Survey of India, Central National Herbarium. Reproduced with permission]
Roadmap for Developing a Dynamic and Reproducible Research Article with ARTE workflow
<p>The figures illustrates a roadmap for developing a dynamic and reproducible research article using <strong>ARTE (Article Reproducibility Template & Environment) </strong>workflow. The process is categorized into three levels of reproducibility: <strong>Minimal, Proper, and Full</strong>. Each level integrates specific tools and practices to enhance the reproducibility of the research.</p> <p>This proposal is published in the following <strong>OSF project</strong>: <a title="OSF" href="https://osf.io/njdq5/" target="_blank" rel="noopener">https://osf.io/njdq5/</a><br>Shared in the following <strong>GitHub repository</strong>: <a title="GitHub" href="https://github.com/phdpablo/article-template" target="_blank" rel="noopener">https://github.com/phdpablo/article-template</a><br>Exemplified in the following <strong>URL address</strong>: <a title="Article Example" href="https://phdpablo.github.io/article-template/" target="_blank" rel="noopener">https://phdpablo.github.io/article-template/</a></p> <h1>Minimal Reproducibility</h1> <p><strong>1. Use this template</strong>: Start by utilizing the provided template, which is pre-configured with the <strong>TIER Protocol 4.0</strong>. This protocol helps organize research projects in a systematic manner.</p> <p><strong>2. Edit READMEs</strong>: Customize the README files to reflect the details and conclusions of your research. These README files help document the project structure and contents.</p> <p><strong>3. Share on OSF</strong>: Share the project on the <strong>Open Science Framework (OSF)</strong> to ensure accessibility and transparency. This can be done at the beginning, during, or at the end of the research process.</p> <h1>Proper Reproducibility</h1> <p>In addition to the steps mentioned above, the following steps are added:</p> <p><strong>4. Quarto settings:</strong> Adjust the Quarto configuration to fit the needs of your project. This includes modifying the <em>_quarto.yml</em> file for different themes and output formats.</p> <p><strong>5. Develop your narrative</strong>: Write the research narrative using <em>Quarto’s .qmd files</em> within RStudio. This narrative forms the main body of your article and integrates text, code, and outputs seamlessly.</p> <p><strong>6. Environment control:</strong> Implement environment control using the <em>renv package</em>. This ensures that the R environment is consistent and reproducible. The <em>renv.lock</em> file captures the exact versions of R packages used in the project.</p> <p><strong>7. Share dynamic article:</strong> Render and share the dynamic document via GitHub Pages. The Quarto-generated HTML files (docs folders) are hosted on GitHub Pages, making the research accessible and interactive.</p> <h1>Full Reproducibility</h1> <p>Building on the proper reproducibility steps, full reproducibility adds:</p> <p><strong>8. Use Docker:</strong> Employ Docker for operating system-level environment control. A Docker container encapsulates the entire project environment, ensuring that the research can be replicated exactly, regardless of the local machine setup.</p> <h2>Tools Utilized</h2> <ul> <li><strong>TIER Protocol 4.0</strong>: Provides a framework for organizing and documenting research projects.</li> <li><strong>OSF:</strong> A platform for sharing research outputs and ensuring open science practices.</li> <li><strong>Quarto:</strong> A tool for creating dynamic documents that integrate text, code, and outputs.</li> <li><strong>RStudio:</strong> An integrated development environment (IDE) for R, facilitating data analysis and reproducible research.</li> <li><strong>Git/GitHub:</strong> Version control systems that track changes and manage project versions.</li> <li><strong>renv: </strong>An R package for managing and reproducing consistent R environments.</li> <li><strong>GitHub Pages:</strong> A service for hosting static websites directly from a GitHub repository.</li> <li><strong>Docker:</strong> A platform for containerizing applications to ensure consistent environments across different systems.</li> </ul> <h2>Summary</h2> <p>This template guides researchers through creating a reproducible and dynamic article using ARTE (Article Reproducibility Template & Environment) workflow. It starts with basic project setup and documentation, progresses through developing the research narrative with environment control, and culminates in full reproducibility with Docker. This structured approach ensures that research is well-documented, versioned, and easily shareable, promoting open science practices.</p>
Data for SI-Hg D2 validation report for the calibration of elemental mercury gas generators including information on repeatability, reproducibility and uncertainty evaluation at emission and ambient levels extended to the sub ng/m3 level
<p>In deliverable 2 of the SI-Hg project the first validation results of the SI-Hg calibration protocol are reported. Within the SI-Hg project a protocol for the metrological calibration of elemental mercury gas generators used in the field was developed. For the validation the output of two different mercury gas generators was calibrated according to the protocol. As metrological reference standard the primary mercury gas standard from the Van Swinden Laboratory (VSL) was used. The measurements described in the protocol could be performed during the validation and the data was processed using a script to determine the output of the candidate generator and the uncertainty of the mercury concentration. Based on the validation measurements and data processing several improvements for the calibration protocol were identified and were used to improve the calibration protocol. </p><p>In this repository data obtained during the validation is published. The files of the following comparisons between reference generator and candidate generator can be found in this repository:</p><ul><li>VSL vs VSL<ul><li>m1<ul><li>09022022 calibration mercury gas generator VSL vs VSL m1</li><li>VSL_vs_VSL_m1</li></ul></li><li>m2 <ul><li>05072022 calibration mercury gas generator VSL vs VSL m2</li><li>VSL_vs_VSL_m2</li></ul></li><li>m3<ul><li>07072022 calibration mercury gas generator VSL vs VSL m3</li><li>VSL_vs_VSL_m3</li></ul></li></ul></li><li>VSL vs PSA before modification<ul><li>m1<ul><li>15032022 calibration mercury gas generator VSL vs PSA fixed m1</li><li>single_point_VSL_vs_PSA_fixed_m1_4</li><li>single_point_VSL_vs_PSA_fixed_m1_6</li><li>single_point_VSL_vs_PSA_fixed_m1_8</li><li>single_point_VSL_vs_PSA_fixed_m1_12</li></ul></li><li>m2<ul><li>28032022 calibration mercury gas generator VSL vs PSA fixed m2</li><li>single_point_VSL_vs_PSA_fixed_m2_4</li><li>single_point_VSL_vs_PSA_fixed_m2_6</li><li>single_point_VSL_vs_PSA_fixed_m2_8</li><li>single_point_VSL_vs_PSA_fixed_m2_12</li></ul></li><li>m3 <ul><li>06042022 calibration mercury gas generator VSL vs PSA fixed m3</li><li>single_point_VSL_vs_PSA_fixed_m3_4</li><li>single_point_VSL_vs_PSA_fixed_m3_6</li><li>single_point_VSL_vs_PSA_fixed_m3_8</li><li>single_point_VSL_vs_PSA_fixed_m3_12</li></ul></li><li>m4 <ul><li>12042022 calibration mercury gas generator VSL vs PSA fixed m4</li><li>single_point_VSL_vs_PSA_fixed_m4_4</li><li>single_point_VSL_vs_PSA_fixed_m4_6</li><li>single_point_VSL_vs_PSA_fixed_m4_8</li><li>single_point_VSL_vs_PSA_fixed_m4_12</li></ul></li><li>less tubing <ul><li>14042022 calibration mercury gas generator VSL vs PSA fixed less tubing</li><li>single_point_VSL_vs_PSA_fixed_less_tubing</li></ul></li><li>less tubing and air as complementary gas <ul><li>19042022 calibration mercury gas generator VSL vs PSA fixed less tubing in air</li><li>single_point_VSL_vs_PSA_fixed_less_tubing_air</li></ul></li></ul></li><li>VSL vs PSA after modification<ul><li>m1 air as complementary gas <ul><li>Calibration PSA fixed mercury gas generator air m1 20230324</li><li>PSA_fixed_air_m1_9</li><li>PSA_fixed_air_m1_11</li><li>PSA_fixed_air_m1_14</li></ul></li><li>m2 air as complementary gas <ul><li>Calibration PSA fixed mercury gas generator air m2 20230327</li><li>PSA_fixed_air_m2_9</li><li>PSA_fixed_air_m2_11</li><li>PSA_fixed_air_m2_14</li></ul></li><li>m3 air as complementary gas <ul><li>Calibration PSA fixed mercury gas generator air m3 20230329</li><li>PSA_fixed_air_m3_9</li><li>PSA_fixed_air_m3_11</li><li>PSA_fixed_air_m3_14</li></ul></li><li>m4 air as complementary gas <ul><li>Calibration PSA fixed mercury gas generator air m4 20230907</li><li>PSA_fixed_air_m4_9</li><li>PSA_fixed_air_m4_11</li><li>PSA_fixed_air_m4_14</li></ul></li><li>m5 air as complemantary gas <ul><li>Calibration PSA fixed mercury gas generator air m5 20230911</li><li>PSA_fixed_air_m5_9</li><li>PSA_fixed_air_m5_11</li><li>PSA_fixed_air_m5_14</li></ul></li><li>m1 nitrogen (N2) as complementary gas<ul><li>Calibration PSA fixed mercury gas generator nitrogen m1 20230330</li><li>PSA_fixed_N2_m1_9</li><li>PSA_fixed_N2_m1_11</li><li>PSA_fixed_N2_m1_14</li></ul></li><li>m2 N2 as complementary gas <ul><li>Calibration PSA fixed mercury gas generator nitrogen m2 20230331</li><li>PSA_fixed_N2_m2_9</li><li>PSA_fixed_N2_m2_11</li><li>PSA_fixed_N2_m2_14</li></ul></li><li>m3 N2 as complementary gas <ul><li>Calibration PSA fixed mercury gas generator nitrogen m3 20230405</li><li>PSA_fixed_N2_m3_9</li><li>PSA_fixed_N2_m3_11</li><li>PSA_fixed_N2_m3_14</li></ul></li><li>measurement at TUV<ul><li>PSA_Fixed_at_TUV</li></ul></li></ul></li></ul>
Reproducibility code and data - Understanding cetacean habitats in the Eastern Caribbean: a study combining data from multiple sources
<p>This R project reproduces the analyses carried out in the article entitled “Modelling cetacean habitats in the Eastern Caribbean: a study combining data from multiple sources” submitted to PCI Ecology. Analyses involve two steps (modelling 1: exploratory; and modelling 2: inferential).</p>
Reproducibility Package: Automata-Driven Partial Order Reduction and Guided Search for LTL
<p>Reproducibility package for the paper <strong>Automata-Driven Partial Order Reduction and Guided Search for LTL Model Checking</strong> accepted for VMCAI'22.</p> <p>Contains scripts, 64-bit Linux binaries, and the dataset used to run the experiments detailed in the paper, a source code snapshot used to compile those binaries, as well as scripts for processing the results into the tables seen in the paper. The file README.md contains details on running the various parts of the artifacts, assuming a Linux environment.</p>
Towards a reproducible interactome: semantic-based detection of redundancies to unify protein-protein interaction databases
<p>Protein-protein interactions (PPIs) play an ubiquitous and fundamental role in all biological processes. Information on PPIs described in the literature is annotated and made available by several protein-interaction databases. Because most databases have their own curation rules and priorities, they often annotate overlapping sets of publications, which leads to redundancies. We developed a semantic-based approach which enables to accurately detect redundancies within PPI datasets from multiple databases. We applied this approach to assemble a "reproducible interactome", with PPIs supported by at least two methods or publications.</p>
Alchemical Free Energy Estimators and Molecular Dynamics Engines: Accuracy, Precision and Reproducibility - Dataset
<p>This zip contains all input structures for paper the: Alchemical Free<br> Energy Estimators and Molecular Dynamics<br> Engines: Accuracy, Precision and Reproducibility</p> <p>Authors: Alexander D. Wade, Agastya P. Bhati, Shunzhou Wan, Peter V.Coveney</p> <p>The structures of the folders are protein/ligand_transformation/alchemical_leg/input/files</p> <p>The ligand transformation are derived from previous work by wang et al. (https://pubs.acs.org/doi/10.1021/ja512751q)</p> <p>There are two files for the solvent alchemical leg: complex.pdb and complex.prmtop</p> <p>complex.pdb is structure file that also denotes the alchemical atoms in the pdb beta column. complex.prmtop is an AMBER parameter/topology file</p> <p>For the complex alchemical leg there is an additional file constraints.pdb that contains the constraint information in the pdb beta column.</p> <p>These files can be used with TIES_MD (https://ucl-ccs.github.io/TIES_MD/) or other molecular dynamics engiens that take AMBER input.</p>
Heatwave breaks down the linearity between sun-induced fluorescence and gross primary production. Reproducible workflow
<p>Dataset for manuscript entitled "Heatwave breaks down the linearity between sun-induced fluorescence and gross primary production" accepted for publication in New Phytologist. The dataset was obtained for the site Majadas del Tietar, Spain, between June/2018 and August/2018. It consists of eddy covariance data, sun-induced fluorescence data and active fluorescence data. </p>
Reproducing nonlinear seismic response from in-situ soil dynamic parameters: application to the Delaney Park Downhole Array, Alaska
<p>The zip file named 'seismic data at DPDA.zip' contains all the seismic data used in our study.</p> <p>The DEEPSOIL file named 'ground response analysis at DPDA.dp' contains the numerical models used in our study.</p>
Elements of Style in Reproducible Workflow Creation and Analysis: An INCLUDE Training Event
<p><a href="https://github.com/NIH-NICHD/Elements-of-Style-Workflow-Creation-Maintenance/blob/main/README.md">Elements of Style Workflow Creation and Maintenance</a>: An INCLUDE Training Event</p> <p>The <a href="https://includedcc.org/">INCLUDE Data Hub</a> is a new resource that securely hosts human clinical, genomic, transcriptomic, proteomic, and other data providing a wealth of opportunities to study conditions that affect individuals with Down syndrome. Today, the approach to answering new scientific questions with these data often uses cloud-based methods accessible through web browsers.</p> <p>During a three-hour virtual training, users learn the know-how to ask scientific questions with these data using cloud platforms and workflows. Users will learn how to build and share processes that assure reproducibility, repurposablility regardless of the computational environment. While many things are possible, the user will be oriented to approaching their work in a modular, testable fashion. </p>
Data to reproduce: "The Seismic Signature of California's Largest Earthquakes, Droughts, and Floods"
<p>Data to reproduce "The Seismic Signature of California's Largest Earthquakes, Droughts, and Floods", submitted to JGR: Solid Earth.</p>
Data to reproduce the results presented in Sehgal et al. 2022. Water Resources Research, https://doi.org/10.1029/2021WR030624 ("Inferring suspended sediment carbon content and particle size at high-frequency from the optical response of a submerged spectrometer")
<p>This repository consists data to reproduce results as presented in: "Inferring suspended sediment carbon content and particle size at high-frequency from the optical response of a submerged spectrometer", Water Resorces Research. Kindly refer to the readme.text file to navigate through the dataset.</p> <p> </p> <p> </p>
Data, analytical, and plotting codes needed to reproduce meta-analyses on within-season divorce in birds
<p>This data package contains data (effect sizes and other variables) and analytical codes needed to reproduce three meta-analyses on within-season divorce and breeding success in socially monogamous birds (Culina & Brouwer: No evidence of immediate fitness benefits of within-season divorce in monogamous birds. 2022. Biology Letters.) It also contains codes to reproduce Figures from the main text and from the Supplement. Readme file and Licence are provided too.</p>
PyKEEN Reproducibility Experiment Model Files
This repository provides weights of the models from the reproducibility study conducted in <a href="https://arxiv.org/abs/2006.13365">"Bringing Light Into the Dark: A Large-scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework"</a> which have been upgraded to compatible with <a href="https://github.com/pykeen/pykeen/releases/tag/v1.9.0">PyKEEN 1.9</a>.
Image data for bioRxiv article named: mtFociCounter - Reproducible, open source and quantitative single-cell analysis of mitochondrial nucleoids and other foci
<p>Raw imaging data to reproduce and test the findings of the bioRxiv article: <strong>mtFociCounter </strong>- Reproducible, open source and quantitative single-cell analysis of mitochondrial nucleoids and other foci. It contains data from three imaging days and 2 or three technical replicates on each day.</p> <p> </p>
Data to reproduce: Cultural diffusion dynamics depend on behavioral production rules
<p>This repository contains data to reproduce the manuscript titled "Cultural diffusion dynamics depend on behavioural production rules". These RDAs contain simulation data, as well as inference data from NBDA and EWA analyses. They are intended to be used with the analysis code found at <a href="http://www.github.com/michaelchimento/acquisition_production_abm" rel="noopener">www.github.com/michaelchimento/acquisition_production_abm</a>.</p>
Text-fig. 1. The pioneers of scientific palaeobotany whose ideas laid the foundations of how we now name plant fossil-taxa. a: Ernst von Schlotheim (1764 – 1821); b: Kaspar Maria von Sternberg (1761 – 1837), reproduced by permission from J. Kvaček (National Museum, Prague); c: Adolphe Brongniart (1801 – 1876). Adapted from Cleal and Thomas (2019: fig. 2.1). in Naming Of Parts: The Use Of Fossil-Taxa In Palaeobotany
Text-fig. 1. The pioneers of scientific palaeobotany whose ideas laid the foundations of how we now name plant fossil-taxa. a: Ernst von Schlotheim (1764 – 1821); b: Kaspar Maria von Sternberg (1761 – 1837), reproduced by permission from J. Kvaček (National Museum, Prague); c: Adolphe Brongniart (1801 – 1876). Adapted from Cleal and Thomas (2019: fig. 2.1).
Text-fig. 1. Massalongo's original specimens. a: Laminarites irideaephyllus A.MASSAL.; b: Pterigophycos gazolanus A.MASSAL.; c: Pterigophycos canossae A.MASSAL.; d: Pterigophycos spectabilis A.MASSAL. Reproduced from Massalongo (1858: pls 15–17). Scale bars = 1 cm. in A Whole-Plant Specimen Of The Marine Macroalga Pterigophycos From The Eocene Of Bolca (Veneto, N-Italy)
Text-fig. 1. Massalongo's original specimens. a: Laminarites irideaephyllus A.MASSAL.; b: Pterigophycos gazolanus A.MASSAL.; c: Pterigophycos canossae A.MASSAL.; d: Pterigophycos spectabilis A.MASSAL. Reproduced from Massalongo (1858: pls 15–17). Scale bars = 1 cm.
Routine to reproduce the figures from "Experimental study of the flows in a non-axisymmetric ellipsoid under precession"" JFM, 2022
<p>The Zip file contains the python notebook and all necessary datasets to reproduce the figures from the publication:</p> <ol> <li>Burmann, F. and <strong>Noir, J</strong>., 2022. Experimental study of the flows in a non-axisymmetric ellipsoid under precession. <em>Journal of Fluid</em> <em>Mechanics</em>, <em>932</em>,<a href="https://doi.org/10.1017/jfm.2021.932">https://doi.org/10.1017/jfm.2021.932</a></li> </ol> <p>The data are saved in .npz format, the structure of the data is explained in the header of the python jupyter notebook. </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.