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134 results for “association test”
Summary statistics for association tests between human and Plasmodium falciparum genetic variants in 3,346 severe malaria cases from The Gambia and Kenya
<p>This dataset contains summary statistics for association tests between human and<br> <em>Plasmodium falciparum</em> malaria parasite genetic variants, using data from 3,346 severe malaria cases from The Gambia and Kenya. These results underlie the analysis described in our paper:</p> <p><strong>"Malaria protection due to sickle haemoglobin depends on parasite genotype"</strong></p> <p>Gavin Band, Ellen M. Leffler, Muminatou Jallow, Fatoumatta Sisay-Joof, Carolyne M. Ndila, Alexander W. Macharia, Christina Hubbart, Anna E. Jeffreys, Kate Rowlands, Thuy Nguyen, Sónia M. Gonçalves, Cristina V. Ariani, Jim Stalker, Richard D. Pearson, Roberto Amato, Eleanor Drury, Giorgio Sirugo, Umberto d'Alessandro, Kalifa A. Bojang, Kevin Marsh, Norbert Peshu, Joseph W. Saelens, Mahamadou Diakité, Steve M. Taylor, David J. Conway, Thomas N. Williams, Kirk A. Rockett, Dominic P. Kwiatkowski</p> <p>Nature (2021) doi: <a href="https://doi.org/10.1038/s41586-021-04288-3">10.1038/s41586-021-04288-3</a> <strong>bioRxiv link</strong>:: <a href="https://doi.org/10.1101/2021.03.30.437659">doi.org/10.1101/2021.03.30.437659</a><br> <br> The genotype data underlying these summary statistics has also been deposited on Zenodo<br> (<a href="https://zenodo.org/record/4973477">doi:10.5281/zenodo.4973477</a>). The <a href="https://www.well.ox.ac.uk/~gav/hptest)">HPTEST software</a> used to generate these results has also been deposited (<a href="https://doi.org/10.5281/zenodo.5685580">doi:10.5281/zenodo.5685580</a>). Please see the <a href="https://www.malariagen.net/resource/32">MalariaGEN website</a> for a full list of datasets which have been released with this manuscript.</p> <p><strong>Data contents.</strong></p> <p>The dataset consists of a single <a href="http://sqlite.org">sqlite database file</a> containing the results, and an accompanying README file in markdown and html format. Please see the README file for full details of the data contents.</p> <p> </p>
Training and Testing Data, Associated Code, and WRF Code for ML-based nonhydrostatic alternative scheme in dynamical core of atmosphere
<p>Data and codes for a nonhydrostatic alternative scheme (NAS) in dynamical core of atmosphere based on machine learning.</p> <p>In this new version, the randomly sampled training data samples testing data samples from nonhydrostatic simulations in WRF baraclinic wave test are provided. They are processed into a new data structure, which can be directly utilized in training and testing. </p> <p>Follow the instructions in README.txt and download the training and testing data, and the associated codes.</p> <p>Here we provide 3 parts of data and codes:</p> <p>1, Training and testing data from WRF;</p> <p>2, Training and testing codes for two machine learning emulators: machine learning and neural network</p> <p>3, WRF application.</p>
Data associated with the manuscript "Simple statistical models can be sufficient for testing hypotheses with population time series data"
<p>This is a revised version of the archive of R code and data used in the manuscript, <em>Simple statistical models can be sufficient for testing hypotheses with population time series data. </em>The data are in three files. <em>etodata1.csv</em> and <em>etodata2.csv</em> contain two versions of the same data for shoal-dwelling fishes in the Etowah River and associated environmental covariates. <em>knz_dat</em> contains data for small mammals collected in the Konza Prairie Biological Station and associated environmental covariates. The R code consists of four primary files that call nine auxiliary files. CaseStudy1-main_code and CaseStudy2-main_code are the primary files for running the two case studies. Simulations1 and Simulations2 are the files for running the two batteries of simulations. We thank the Konza Prairie Biological Station and Konza Prairie Long-Term Ecological Research Program supported by the National Science Foundation (DEB-1440484) for collecting and providing access to mammal community data. More details are in the manuscript and supporting information. </p>
Figure 1 in Testing the Temporal Limits of Lures and Toxicants for Trapping Fruit Flies (Diptera: Tephritidae): Additional Weathering Studies of Solid Bactrocera and Zeugodacus Male Lures and Associated Insecticidal Strips
Figure 1. Captures of Zeugodacus cucurbitae males in Jackson traps containing toxicants of variable age deployed at Aloun Farm, Oahu, Hawaii. The lures were fresh in all traps and were prepared in Hawaii at the start of the test. Two fresh toxicants were included: naled in liquid CL (bar labelled L) and a DDVP strip with a CL plug (bar labelled P). The DDVP strips weathered in Arizona and Florida were tested during the same 1-day period (December 9–10, 2015). Values represent means (+ 1 SE); 12 traps were deployed per treatment. Bars marked by different letters were significantly different (Student-Newman-Keuls multiple comparisons test).
Dataset of Cervical Cell Images for the Study of Changes Associated with Malignancy in Conventional Pap Test
<p>This data set was approved by CEP, a human-research ethics committee {Comitê de Ética em Pesquisa de Campinas}, Brazil <em>(CAAE approval number: 71277217.6.0000.5404) </em></p> <p>Cervical cancer prevention campaign was carried out at the University of Campinas (Brazil), where 71 women were treated. For this study, six women were chosen: non-pre-menopausal, non-pregnant and between the ages of 25 and 40 years. Samples diagnosed with normal squamous lesions, atypia in squamous cells of undetermined significance (AC-US), low-grade squamous intraepithelial lesion LEI (changes associated with HPV infection or light dislocation (NIC 1)), and immature squamous metaplasia, were chosen. All samples were collected before treatment. The patients were anonymized and assigned a unique identifier. The criterion to limit the number of plates used in this study is related to the large amount of data to be processed and the computational cost necessary for this process.</p> <p>Raw data sets are available as CSV files. Each data was numbered to include the identification of the meta-data, along with the tag of the images following a sequence. For example, the data file<em> “ 01-CAP091868-MORF.csv ”</em> has the prefix 01 that refers to the sequential numbering of the files with the data from the digitized slide.</p> <p>The data set contains 102 digitized images of the human papilloma examination of 7 different patients. They were segmented 962</p>
Fig. 3 in Comparison of the modified agglutination test and real-time PCR for detection of Toxoplasma gondii exposure in feral cats from Phillip Island, Australia, and risk factors associated with infection
Fig. 3. Predicted lines of fit for the multivariable logistic regression model plotted as probability of Toxoplasma gondii qPCR positivity in feral cats on Phillip Island (Victoria) versus body weight for each season. Dashed lines show 95% confidence intervals.
Fig. 1 in Comparison of the modified agglutination test and real-time PCR for detection of Toxoplasma gondii exposure in feral cats from Phillip Island, Australia, and risk factors associated with infection
Fig. 1. Location and Toxoplasma gondii infection status, as detected by real-time PCR (qPCR), of feral cats trapped on Phillip Island (Victoria) from July 2016 to December 2017. Map shows the distribution of different location types (Park, Agricultural, Residential) used in multivariable regression analysis. A circular spread of points around a location marked with 'x' indicates multiple animals were sampled at the same site (i.e. same GPS coordinates). Red = T. gondii qPCR positive, white = T. gondii qPCR negative. Map created using Quantum GIS, version 3.8. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Data and Software associated with the paper "``A New Likelihood-based Test for Natural Selection''"
<p>Data and Software associated with the paper ``A New Likelihood-based Test for Natural Selection''</p>
A Study to Test if TEV-50717 is Effective in Relieving Tics Associated With Tourette Syndrome (TS)
ClinicalTrials.gov study NCT03571256. IPD Sharing: YES. Countries: 10. Publications: 1.
Scripts and data sets associated with: On testing homogeneity of the evolutionary process using alignments of homologous sequences
Open the record for dataset details and reuse information.
Dataset: Survey on the actual situation of antibiotic resistant bacteria detection by nucleic acid amplification test in clinical microbiology laboratories at hospitals in Japan: Online survey of participants in workshops organized by the Nara Association of Medical Technologists
<p>The coronavirus disease 2019 pandemic has led to the widespread use of the nucleic acid amplification test (NAAT), along with an increase in demand for SARS-CoV-2 tests. NAAT has been used to detect antimicrobial resistance (AMR) genes since before the pandemic, but the test has been performed in a limited number of facilities. We investigated the current status and background of Japanese clinical laboratories by surveying the implementation of genotypic AST in NAAT, which has become widespread owing to the pandemic. This means that 59% of the respondents possessed NAAT and were using it for genotypic AST. GeneXpert and FilmArray were introduced in the majority of cases (62.5% and 82.6%, respectively), with the pandemic as the trigger. More than half of the respondents cited “rapid detection” (56.0%) and “ICT requests” (52.4%) as the reasons for introducing the system. Regarding usefulness, “contribution to infectious disease treatment” (74.1%) showed the highest percentage. Among the respondents who cited “not implemented”, the most frequent responses were “I have no plans, but I want to do it.” (38.1%) and “would do so if requested by a physician” (33.3%). The most common reason for not implementing the system was concern about increased workload (52.9%). We believe that this is due to changes in the working environment caused by the pandemic and the characteristics of Japanese society. In the future, to promote the adoption of genotypic AST, it will be necessary to approach it through reports on its usefulness from domestic facilities, and simultaneously, improving and enhancing efficiency in work processes will also be essential.</p>
Comparing mixed models and Random Forest association tests using naturalGWAS and a Striped Bass SNP dataset
<p>In this study, we used the phenotype simulation package naturalGWAS to test the performance of Zhao's Random Forest method in comparison to an uncorrected Random Forest test, latent factor mixed models (LFMM), genome-wide efficient mixed models (GEMMA), and confounder adjusted linear regression (CATE). We created 400 sets of phenotypes, corresponding to five effect sizes and 2, 5, 15, or 30 causal loci, simulated from two empirical datasets containing SNPs from Striped Bass representing three and 13 populations. All association methods were evaluated for their ability to detect genotype-phenotype associations based on power, false discovery rates, and number of false positives. Genomic inflation was highest for uncorrected Random Forest and LFMM tests and lowest for Gemma and Zhao's Random Forest. All association tests had similar power to detect causal loci, and Zhao's Random Forest had the lowest false discovery rate in all scenarios. To measure the performance of association tests in small datasets with few loci surrounding a causal gene we also ran analyses again after removing causal loci from each dataset. All association tests were only able to find true positives, defined as loci located within 30k bp of a causal locus, in 3%–18% of simulations. In contrast, at least one false positive was found in 17%–44% of simulations. Zhao's Random Forest again identified the fewest false positives of all association tests studied. The ability to test the power of association tests for individual empirical datasets can be an extremely useful first step when designing a GWAS study.</p>
Training and testing data, associated code and estimators for emulating a convection scheme
<p>Data and code for a random-forest convection scheme associated with the paper:</p> <p>"Using machine learning to parameterize moist convection: potential for modeling of climate, climate change and extreme events"</p> <p>by Paul A. O'Gorman and John G. Dwyer (to appear in JAMES)</p>
DeepRVAT gene-trait association testing results on the 470k UK Biobank WES dataset
<p>Association testing results from DeepRVAT on the 470k UK Biobank WES dataset, covering all tested genes and traits. Tests were performed on the full dataset and on Caucasian individuals ("cohort" column). "Significant" indicates significance after multiple testing correction (FWER < 5%).</p>
PLINK association test statistics of UK Biobank blood traits
<p>PLINK association test statistics of UK Biobank blood traits generated for mvSuSiE fine-mapping analyses; see https://www.biorxiv.org/content/10.1101/2023.04.14.536893.</p>
A Study to Test the Effects of Riociguat in Patients With Pulmonary Hypertension Associated With Left Ventricular Systolic Dysfunction
ClinicalTrials.gov study NCT01065454. IPD Sharing: NO. Countries: 18. Publications: 2.
Testing New Strategies for Patients Hospitalised With HIV-associated Disseminated Tuberculosis
ClinicalTrials.gov study NCT04951986. IPD Sharing: YES. Countries: 1. Publications: 1.
A Study to Test Whether Nintedanib Influences the Components of Birth-control Pills in Women With Systemic Sclerosis Associated Interstitial Lung Disease (SSc-ILD)
ClinicalTrials.gov study NCT03675581. IPD Sharing: UNDECIDED. Countries: 6. Publications: 1.
Comparing mixed models and Random Forest association tests using naturalGWAS and a Striped Bass SNP dataset
Open the record for dataset details and reuse information.
Training and Testing Data, Associated Code, and SCAM Validations Code and Data for ResNet in moist physics (ResCu)
<p>Data and codes for a deep convolutional residual neural network moist physics parameterization (ResCu).</p> <p>In this new version, the randomly selected training data samples and part of testing data samples (June, July and August) are provided. They are processed into a new data structure, which can be directly utilized in training and testing. For the entire second year training samples and the entire third year testing samples, we provide them in a repository at Dryad (<a href="https://doi.org/10.6075/J0CZ35PP">https://doi.org/10.6075/J0CZ35PP</a> and https://doi.org/10.6075/J03J3BGF).</p> <p>Please download and decompress ResCu_Han_et_al_JAMES.tar.gz.</p> <p>Follow the instructions in README.txt and download the training and testing data (The Dryad depositary is provided in the description). </p> <p>Here we provide 3 parts of data and codes:</p> <p>1, Training and testing data from SPCAM;</p> <p>2, Training and testing codes for ResCu and many other NN architectures;</p> <p>3, SCAM validations.</p> <p> </p>
ScienceDex guides
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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.