Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
173
datasets available to search
ShareScore release 0.9.0
Dataset results
173 results for “Statistical analysis”
Figure 3 in Statistical analysis on the cnidome of genus Hydra using Generalized Linear Models
Figure 3. Cnidome of Hydra vulgaris pedunculata. (A) stenotele, (B) desmoneme, (C) atrichous isorhiza and (D) holotrichous isorhiza. Scale bar: 2.7 μm.
Figure 2 in Statistical analysis on the cnidome of genus Hydra using Generalized Linear Models
Figure 2. Cnidome of Hydra vulgaris. (A) stenotele, (B) desmoneme, (C) atrichous isorhiza and (D) holotrichous isorhiza. Scale bar: 2.85 μm.
Unwarranted Inferences from Statistical Mediation Tests – An Analysis of Articles Published in 2015
<p>Recent attempts to improve on the quality of psychological research focus on good practices required for statistical<br> significance testing. The scrutiny of theoretical reasoning, though superordinate, is largely neglected, as<br> exemplified here in a common misunderstanding of mediation analysis. Although a test of a mediation model<br> X -> Z -> Y is conditional on the premise that the model applies, alternative mediators Z′, Z″, Z‴ etc. remain<br> untested, and other causal models could underlie the correlation between X, Y, Z, researchers infer from a single<br> significant mediation test that they have identified the true mediator. A literature search of all mediation analyses<br> published in 2015 in Sciencedirect shows that the vast majority of studies neither consider alternative causal<br> models nor alternative mediator candidates. Ignoring that mediation analysis is conditional on the truth of the<br> focal mediation model, they pretend to have demonstrated that Z mediates the influence of X on Y. Recommendations<br> are provided for how to overcome this dissatisfying state of affairs.</p>
96 wells fluorescence reading and R code statistic for analysis
<p><strong>Overview</strong></p> <p>Data points present in this dataset were obtained following the subsequent steps: To assess the secretion efficiency of the constructs, 96 colonies from the selection plates were evaluated using the workflow presented in Figure Workflow. We picked transformed colonies and cultured in 400 μL TAP medium for 7 days in Deep-well plates (Corning Axygen®, No.: PDW500CS, Thermo Fisher Scientific Inc., Waltham, MA), covered with Breathe-Easy® (Sigma-Aldrich®). Cultivation was performed on a rotary shaker, set to 150 rpm, under constant illumination (50 μmol photons/m<sup>2</sup>s). Then 100 μL sample were transferred clear bottom 96-well plate (Corning Costar, Tewksbury, MA, USA) and fluorescence was measured using an Infinite® M200 PRO plate reader (Tecan, Männedorf, Switzerland). Fluorescence was measured at excitation 575/9 nm and emission 608/20 nm. Supernatant samples were obtained by spinning Deep-well plates at 3000 × <em>g</em> for 10 min and transferring 100 μL from each well to the clear bottom 96-well plate (Corning Costar, Tewksbury, MA, USA), followed by fluorescence measurement. To compare the constructs, R Statistic version 3.3.3 was used to perform one-way ANOVA (with Tukey's test), and to test statistical hypotheses, the significance level was set at 0.05. Graphs were generated in RStudio v1.0.136. The codes are deposit herein.</p> <p> </p> <p><strong>Info</strong></p> <p>ANOVA_Turkey_Sub.R -> code for ANOVA analysis in R statistic 3.3.3</p> <p>barplot_R.R -> code to generate bar plot in R statistic 3.3.3</p> <p>boxplotv2.R -> code to generate boxplot in R statistic 3.3.3</p> <p>pRFU_+_bk.csv -> relative supernatant mCherry fluorescence dataset of positive colonies, blanked with parental wild-type cc1690 cell of <em>Chlamydomonas reinhardtii</em> </p> <p>sup_+_bl.csv -> supernatant mCherry fluorescence dataset of positive colonies, blanked with parental wild-type cc1690 cell of <em>Chlamydomonas reinhardtii</em> </p> <p>sup_raw.csv -> supernatant mCherry fluorescence dataset of 96 colonies for each construct.</p> <p>who_+_bl2.csv -> whole culture mCherry fluorescence dataset of positive colonies, blanked with parental wild-type cc1690 cell of <em>Chlamydomonas reinhardtii</em> </p> <p>who_raw.csv -> whole culture mCherry fluorescence dataset of 96 colonies for each construct.</p> <p>who_+_Chlo.csv -> whole culture chlorophyll fluorescence dataset of 96 colonies for each construct.</p> <p>Anova_Output_Summary_Guide.pdf -> Explain the ANOVA files content</p> <p>ANOVA_pRFU_+_bk.doc -> ANOVA of relative supernatant mCherry fluorescence dataset of positive colonies, blanked with parental wild-type cc1690 cell of <em>Chlamydomonas reinhardtii</em> </p> <p>ANOVA_sup_+_bk.doc -> ANOVA of supernatant mCherry fluorescence dataset of positive colonies, blanked with parental wild-type cc1690 cell of <em>Chlamydomonas reinhardtii</em> </p> <p>ANOVA_who_+_bk.doc -> ANOVA of whole culture mCherry fluorescence dataset of positive colonies, blanked with parental wild-type cc1690 cell of <em>Chlamydomonas reinhardtii</em> </p> <p>ANOVA_Chlo.doc -> ANOVA of whole culture chlorophyll fluorescence of all constructs, plus average and standard deviation values.</p> <p> </p> <p><strong>Consider citing our work. </strong></p> <p>Molino JVD, de Carvalho JCM, Mayfield SP (2018) Comparison of secretory signal peptides for heterologous protein expression in microalgae: Expanding the secretion portfolio for Chlamydomonas reinhardtii. PLoS ONE 13(2): e0192433. https://doi.org/10.1371/journal. pone.0192433</p> <p> </p> <p> </p>
Seven Fluorescent proteins profile in Chlamydomonas reinhardtii and R code statistic for analysis
<p><strong>Overview</strong></p> <p>Data points present in this dataset were obtained following the protocol described in dx.doi.org/10.17504/protocols.io.kfnctme. We picked transformed colonies and cultured in 400 μL TAP medium for 7 days in Deep-well plates (Corning Axygen®, No.: PDW500CS, Thermo Fisher Scientific Inc., Waltham, MA), covered with Breathe-Easy® (Sigma-Aldrich®). Cultivation was performed on a rotary shaker, set to 150 rpm, under constant illumination (50 μmol photons/m<sup>2</sup>s). Then 100 μL sample were transferred clear bottom 96-well plate (Corning Costar, Tewksbury, MA, USA) and fluorescence was measured using an Infinite® M200 PRO plate reader (Tecan, Männedorf, Switzerland). Supernatant samples were obtained by spinning Deep-well plates at 3000 × <em>g</em> for 10 min and transferring 100 μL from each well to the clear bottom 96-well plate (Corning Costar, Tewksbury, MA, USA), followed by fluorescence measurement. To compare the constructs, R Statistic version 3.3.3 was used to perform one-way ANOVA (with Tukey's test), and to test statistical hypotheses, the significance level was set at 0.05. Graphs were generated in RStudio v1.0.136. The codes are deposit herein.</p> <p><strong>Info</strong></p> <p>ANOVA_Turkey_Sub.R -> code for ANOVA analysis in R statistic 3.3.3</p> <p>Anova_Output_Summary_Guide.pdf -> Explain the ANOVA files content</p> <p>Analysis_Raw_FP.xlsx -> File with raw values organized in a spreadsheet </p> <p>pRFU_<strong>FLUORESCENT PROTEIN</strong>_+_bk.csv -> relative supernatant mCherry fluorescence dataset of positive colonies, blanked with parental wild-type cc1690 cell of <em>Chlamydomonas reinhardtii </em></p> <p>sup_RFU_<strong>FLUORESCENT PROTEIN_</strong>+_bk.csv -> supernatant mCherry fluorescence dataset of positive colonies, blanked with parental wild-type cc1690 cell of <em>Chlamydomonas reinhardtii</em> </p> <p>who_RFU_<strong>FLUORESCENT PROTEIN_</strong>+_bk.csv -> whole culture mCherry fluorescence dataset of positive colonies, blanked with parental wild-type cc1690 cell of <em>Chlamydomonas reinhardtii</em> </p> <p>pRFU_<strong>FLUORESCENT PROTEIN</strong>_+_bk.doc -> ANOVA of relative supernatant mCherry fluorescence dataset of positive colonies, blanked with parental wild-type cc1690 cell of <em>Chlamydomonas reinhardtii</em> </p> <p>sup_RFU_<strong>FLUORESCENT PROTEIN_</strong>+_bk.doc -> ANOVA of supernatant mCherry fluorescence dataset of positive colonies, blanked with parental wild-type cc1690 cell of <em>Chlamydomonas reinhardtii</em> </p> <p>who_RFU_<strong>FLUORESCENT PROTEIN_</strong>+_bk.doc -> ANOVA of whole culture mCherry fluorescence dataset of positive colonies, blanked with parental wild-type cc1690 cell of <em>Chlamydomonas reinhardtii</em> </p> <p> </p> <p><strong>Consider citing our work. </strong></p> <p>1. Molino JVD, de Carvalho JCM, Mayfield S. Evaluation of secretion reporters to microalgae biotechnology: blue to red fluorescent proteins. Algal Res. 2018;31: 252–261. doi:10.1016/j.algal.2018.02.018</p>
The metabolomics raw data and a supporting statistical analyses data set for publication: Metabolomic analysis revealed the absence of the principal antimicrobial compound of Pseudomonas donghuensis P482, 7-hydroxytropolone, under restricted nutrient conditions.
<p><a href="../api/records/11220997/draft/files/Metabolomic%20analyses%20raw%20files.zip/content" target="_blank" rel="noopener noreferrer">Metabolomic analyses raw files</a>, Compounds analyses, Hierarchical Condition tress and PCA Scores are uploaded.</p>
Statistical analysis flumequine as a fluoroquinolone
<p>This repository is containing the datasets with statistical analysis of the paper: "Flumeqiune, fluoroqiunolone in disguise."</p> <p><em>Sample size calculation with CRITSize</em></p> <ul> <li>R-file: Calculation of swabs</li> </ul> <p><em>Long term exposure experiment</em></p> <ul> <li>R-file: Correlation between resistance and treatment long term exposure</li> <li>XLSX-file: Treatment flumequine, Treatment enrofloxacin</li> </ul> <p><em>Fermentation analysis</em></p> <ul> <li>one R-file: Fermentation experiment</li> <li>one CSV-files: Treatment flumequine, Treatment enrofloxacin</li> </ul> <p><em>Therapeutic concentration of flumequine analysis</em></p> <ul> <li>one R-file: Flumequine field study</li> <li>one CSV-files: Flumequine field study</li> </ul>
Statistical Analysis of Selected Mixtures of Alkali-activated Materials Exposed to Thermal
<p>Alkaline-activated materials have come to the forefront of the interest of construction experts in recent decades.<br>It is a composite material, an alternative to concrete, where the binder component can be a by-product (with pozzolanic or<br>latent hydraulic properties) of some industrial processes instead of ecologically disadvantageous cement. The work is<br>focused on the statistical analysis of the compressive strength of alkali-activated materials exposed to temperature stress,<br>where the first part contains three mixtures of alkali-activated composites that were subjected to the frost resistance test,<br>and the second part follows the functional dependence of the compressive strength of the selected mixture of the alkaliactivated system on exposure to high temperatures with the selection of the optimal statistical model.</p>
Synthetic meshes of hippocampi, for statistical shape analysis validation
<p>Those synthetic data have been generated for the validation of the iterative centroid method published in "Statistical shape analysis of large datasets based on diffeomorphic iterative centroids", which code can be found here: https://github.com/cclairec/Iterative_Centroid</p> <p>The 50 random populations are all generated from a same shape S0. We generated random deformations around S0 and symmetrised the deformations, so the centre of the populations is S0. More details in the paper.</p> <p>Each data set is composed by 50 shapes. The Matlab files contain:</p> <p>- moment: The initial momentum vector used to generate each subject of the population</p> <p>- SkelSuj_Rigid: The first line contains the vertices and faces of each subject. The second line contains the parameters to generate the initial momentum vectors and the subjects.</p>
Supplementary tables for "Theme Enrichment Analysis: A Statistical Test for Identifying Significantly Enriched Themes in a List of Stories with an Application to the Star Trek Television Franchise"
<p>Supplementary tables for the manuscript "Theme Enrichment Analysis: A Statistical Test for Identifying Significantly Enriched Themes in a List of Stories with an Application to the Star Trek Television Franchise".</p> <p>Supplementary Information File 1 contains a table of Star Trek TOS/TAS/TNG television series episodes featuring the Klingon alien race. The criterion for inclusion is that the Klingons were deemed by the authors to have been featured throughout the episode in a way that is central to the story plot.</p> <p>Supplementary Information File 2 contains tables of over-represented Literary Theme Ontology version 0.1.1 literary themes in Star Trek TOS/TAS/TNG television series storysets as identified by the hypergeometric test.</p> <p>Supplementary Information File 3 contains tables of over-represented Literary Theme Ontology version 0.1.1 literary themes in Star Trek TOS/TAS/TNG television series storysets as identified by the TF-IDF statistic.</p>
Statistical analysis PAP on deceleration performance
<p>This is the report of the statistical analysis used to investigate the effects of Post-Activation Potentiation on soccer players' deceleration performance.</p>
Images, data, and statistical analysis scripts for review article on cover crop roots
<p>Images, data, and statistical analysis scripts for review article on cover crop roots.</p> <blockquote> <p><strong>Optimization of root traits to provide enhanced ecosystem services in agricultural systems: a focus on cover crops</strong> - [<a href="https://doi.org/10.1111/pce.14247">https://doi.org/10.1111/pce.14247</a>]</p> </blockquote> <ul> <li>Research site, planting, and growth <ul> <li>10/2020 - 04/26/2021 cover crop field trial. DDPSC FRS at Planthaven Farm, O'Fallon, MO 63366 (latitude 38.848240°, longitude -90.686640°). </li> <li>The field was tilled before sowing of cover crops. Seed for each cover crop were spread in using a push seed spreader and were lightly irrigated.</li> <li>Alfalfa (<em>Medicago sativa</em>), dundale pea (<em>Pisum sativum</em>), milkvetch (<em>Astragalus canadensis</em>, <em>Astragalus bisulcatus</em>), crimson clover (<em>Trifolium incarnatum</em>), hairy vetch (<em>Vicia villosa</em>), mustard (<em>Brassica junce</em>a var Mighty Mustard, var Kodiak), barley (<em>Hordeum vulgare</em>), wheat (<em>Triticum aestivum</em>, winter, spring), winter rye (<em>Secale cereale</em>), and triticale (× T<em>riticosecale</em> Wittmack).</li> </ul> </li> <li> <p>Field harvest measurements</p> <ul> <li> <p>Four canopy images were taken across each cover crop row using a Canon 5DS R camera. Images were taken from above each plot at 5ft height manually. Green color was thresholded from the canopy images in batch using OpenCV python script and the percent green cover calculated (Jupiter notebook).</p> </li> <li> <p>Five soil monoliths were excavated using a "shovelomics" approach with an average monolith size of 25.4cm x 25.4cm x 20 cm. The remaining four soil monoliths were destructively analyzed.</p> </li> <li> <p>One soil monolith was imaged using a Canon 50D DLSR camera in a photogrammetry shed. All photogrammetric analysis was conducted using Pix4D mapper software (Pix4D S.A. Prilly, Switzerland), and point cloud cleaning was conducted in CloudCompare V2. 10.2.</p> </li> <li> <p>Cover crop shoots from the remaining soil monoliths were cut and placed into a paper bag for dry biomass determination (60oC for 5 days). A cover crop shoot count was conducted for each monolith with each tiller considered as a shoot for the grasses (barley, wheat, triticale). After cover crop shoot harvesting, a photo was then taken of each soil monolith with remaining weed biomass. A weed score was assigned to each image by one trained researcher with a score 1 low weeds to 5 high weed presence.</p> </li> <li> <p>Soil monoliths were the soaked briefly in water and then the soil washed using a hose keeping the roots. Roots were then scanned on an Epson Expression 12000XL Photo Scanner with transparency unit. Images labeled with "_part" were samples with too many roots for scanning and so were separately weighed. Dry root biomass was taken for the scanned and unscanned roots separately. Root length was determined from images using software RhizoVision Explorer (https://doi.org/10.5281/zenodo.4095629), total root length was estimated using scanned root length and scanned dry biomass with unscanned root biomass.</p> </li> <li> <p>Along each cover crop plot a 10ft trench was dug using a Yanmar Excavator Vi020-6 perpendicular to the row with each trench fully bisecting the plot. Trench was one bucket wide (19 inches) and approximately 36 inches deep in the middle of the row. The five deepest roots that could be observed in the trench wall was measured manually with a tape measure for each cover crop. A garden trowel and shovel were used to excavate and confirm roots in trench wall.</p> </li> <li> <p>Data was analyzed using R Statistics script and raw data used for data processing and figure generation (2021PlantHavenCovercrop_dataprocessing.R). PCA analysis was conducted using the “FactoMineR” package (Husson <em>et al</em>. 2019) to explore the relationships between the traits within the dataset and clustered by family.</p> </li> </ul> </li> </ul> <p>Individual ZIP file contents:</p> <ul> <li><code><strong>2021PlantHavenCovercrop_CanopyImages.zip</strong></code> – Raw canopy images, processed percent green cover images, and Jupiter notebook python script (2021PlantHavenCovercrop_ImageBatchColorThreshold.ipynb).</li> <li><code><strong>2021PlantHavenCovercrop_RootFlatbedImages.zip</strong></code> – Raw flatbed root scans of cover crops and processed images using RhizoVision Explorer.</li> <li><code><strong>2021PlantHavenCovercrop_SoilMonolithWeedImages.zip</strong></code> – Images of soil monoliths after cover crop shoot biomass was removed.</li> <li><code><strong>2021PlantHavenCovercrop_dataprocessing.zip</strong></code> – R Statistics script and raw data used for data processing and figure generation (2021PlantHavenCovercrop_dataprocessing.R).</li> <li><code><strong>2021PlantHavenCovercrop_ShootPhotogrammetry.zip</strong></code> – 3D models of cover crop shoots from excavated soil monoliths. The .bin files can be opened using CloudCompare app.</li> </ul> <p> </p> <p> </p>
Multidimensional Statistical Technique for Interpreting the Spontaneous Breakthrough Cancer Pain Phenomenon. A Secondary Analysis from the IOPS-MS Study
<p>Simple Summary: Pain is one of the most common and debilitating symptoms in cancer patients. A clinical peculiarity of cancer pain is the breakthrough cancer pain (BTcP), which is defined as a temporary exacerbation of pain that “breaks through” a phase of adequate pain control by an opioid-based therapy. The NP-BTcP occurs in the absence of any specific activity. In this paper, we addressed the topic through a mathematical approach to provide many indications for identifying the diagnostic and therapeutic gaps in NP-BTcP management. Abstract: Breakthrough cancer pain (BTcP) is a temporary exacerbation of pain that “breaks through” a phase of adequate pain control by an opioid-based therapy. The non-predictable BTcP (NP-BTcP) is a subtype of BTcP that occurs in the absence of any specific activity. Since NP-BTcP has an important clinical impact, this analysis is aimed at characterizing the NP-BTcP phenomenon through a multidimensional statistical technique. This is a secondary analysis based on the Italian Oncologic Pain multiSetting—Multicentric Survey (IOPS-MS). A correlation analysis was performed to characterize the NP-BTcP profile about its intensity, number of episodes per day, and type. The multiple correspondence analysis (MCA) determined the identification of four groups (phenotypes). A univariate analysis was performed to assess differences between the four phenotypes and selected covariates. The four phenotypes represent the hierarchical classification according to the status of NP-BTcP: from the best (phenotype 1) to the worst (phenotype 4). The univariate analysis found a significant association between the onset time >10 min in the phenotype 1 (37.3%)’ vs. the onset > 10 min in phenotype 4 (25.8%) (p < 0.001). Phenotype 1 was characterized by the gastrointestinal type of cancer (26.4%) with respect to phenotype 4, where the most frequent cancer affected the lung (28.8%) (p < 0.001). Phenotype 4 was mainly managed with rapid-onset opioids, while in phenotype 1, many patients were treated with oral, subcutaneous, or intravenous morphine (56.4% and 44.4%, respectively; p = 0.008). The ability to characterize NP-BTcP can offer enormous benefits for the management of this serious aspect of cancer pain. Although requiring validation, this strategy can provide many indications for identifying the diagnostic and therapeutic gaps in NP-BTcP management.</p> <p> </p>
Data from: Process-based modelling of nonharmonic internal tides using adjoint, statistical, and stochastic approaches. Part II: adjoint frequency response analysis, stochastic models, and synthesis
<p>Meta data updated after publication.</p> <p> </p>
Data from: Process-based modelling of nonharmonic internal tides using adjoint, statistical, and stochastic approaches. Part I: statistical model and analysis of observational data
<p>Meta data updated after publication.</p> <p> </p>
Table 11. Results of statistical calculation of hydroxyproline levels analysis of variance (ANOVA) two way spss 23.00
<p>Table 11. Results of statistical calculation of hydroxyproline levels analysis of variance (ANOVA) two way spss 23.00</p> <p> </p>
Data and analysis result for "A scalable variational approach to characterize pleiotropic components across thousands of human diseases and complex traits using GWAS summary statistics"
<p>Data set and analysis results from our paper "A scalable variational approach to characterize pleiotropic components across thousands of human diseases and complex traits using GWAS summary statistics" (pre-print). This file contains GWAS summary statistics of 2,483 traits and 51,399 SNP variants from European individuals, originally downloaded and processed from Pan-UK Biobank (https://pan.ukbb.broadinstitute.org/). Additionally, we include results of 100 pleiotropic factors inferred by our method and tSVD as comparison. Please see README for detailed breakdown.</p>
Statistical analysis of the Metal Archives Database
<p>Data, shapefile and R script used to create figures and realize statistical analysis presented in the online paper</p> <p>Laurent Beauguitte et Hugues Pecout, « Les mondes du metal d’après l’Encylopedia Metallum », <em>Volume!</em>, 15(2), 2019, URL : <a href="http://journals.openedition.org/volume/6519">http://journals.openedition.org/volume/6519</a> ; DOI : 10.4000/volume.6519.</p>
Dysregulation of FSH in Obesity: Functional and Statistical Analysis
ClinicalTrials.gov study NCT02478775. IPD Sharing: NO. Countries: 1. Publications: 1.
Experimental and synthetic datasets supporting FITSA: Statistical analysis of fluorescence intensity transients with Bayesian methods
Open the record for dataset details and reuse information.
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.