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328 results for “Analysis results”
Datasets, reproducible codes, and results for evaluating differential expression analysis methods on population-level RNA-seq data
<p>This upload contains the necessary R codes and data to reproduce the FDR and Power results described in our correspondence "Neglecting normalization impact in semi-synthetic RNA-seq data simulation generates artificial false positives" to Li Y, Ge X, Peng F, Li W, Li JJ, Exaggerated false positives by popular differential expression methods when analyzing human population samples, <em>Genome Biology</em> 23, 79, 2022, DOI: 10.1186/s13059-022-02648-4.</p>
Quantitative results of the analysis of relevant components of the human scapholunate interosseous ligament (SLIL)
<p>This dataset corresponds to the quantification results carried out for the human scapholunate interosseous ligament (SLIL) and several control tissues analyzed in the manuscript entitled "Histological characterization of the human scapholunate ligament". The SLIL plays a fundamental role in stabilizing the wrist bones, and its disruption is a frequent cause of wrist arthrosis and disfunction. Traditionally, this structure is considered to be a variety of fibrocartilaginous tissue and consists of three regions: dorsal, membranous and palmar. Despite its functional relevance, the exact composition of the human SLIL is not well understood. In the present work, we have analyzed the human SLIL and control tissues from the human hand using an array of histological, histochemical and immunohistochemical methods to characterize each region of this structure. Results reveal that the SLIL is heterogeneous, and each region can be subdivided in two zones that are histologically different to the other zones. Analysis of collagen and elastic fibers, and several proteoglycans, glycoproteins and glycosaminoglycans confirmed that the different regions can be subdivided in two zones that have their own structure and composition. In general, all parts of the SLIL resemble the histological structure of the control articular cartilage, especially the first part of the membranous region (zone M1). Cells showing a chondrocyte-like phenotype as determined by S100 were more abundant in M1, whereas the zone containing more CD73-positive stem cells was D2. These results confirm the heterogeneity of the human SLIL and could contribute to explain why certain zones of this structure are more prone to structural damage and why other zones have specific regeneration potential. The original data obtained for the quantitative analyses of each component are shown in this dataset.</p>
Results for eQTL and sQTL meta-analysis and colocalization
<p>This dataset is part of the manuscript: "<em>Atlas of genetic effects in human microglia transcriptome across brain regions, aging and disease pathologies</em>", by Lopes KP, Snijders GJL, Humphrey J, et al.</p> <p> </p> <p>Description of files:</p> <p><em>COLOC_supp_table_all_results.tsv.gz - </em>Table with results from <strong>COLOC</strong><em> </em>(gzip-compressed). Table columns are formatted as follows:</p> <ol> <li>disease - disease name (Alzheimer’s disease - AD, Bipolar Disorder - BPD, Multiple sclerosis - MS, Parkinson’s disease - PD, Schizohphrenia - SCZ)</li> <li>GWAS - GWAS study (IMSGC_2019, Jansen_2018, Kunkle_2019, Lambert_2013, Marioni_2018, Nalls23andMe_2019, Ripke_2014, Stahl_2019)</li> <li>locus - locus id according to each GWAS study</li> <li>GWAS_SNP - SNP reported in the GWAS study</li> <li>GWAS_P - <em>P</em>-value of the GWAS_SNP reported in the GWAS study</li> <li>GWAS_chr - chromosome of the GWAS_SNP (hg38)</li> <li>GWAS_pos - genomic position in the chromosome of the GWAS_SNP (hg38)</li> <li>QTL - id for the QTL study</li> <li>type - the type of QTL (eQTL or sQTL)</li> <li>QTL_SNP - SNP id from the QTL association</li> <li>QTL_P - <em>P</em>-value for the QTL association </li> <li>QTL_Beta - Slope (beta) for the QTL association</li> <li>QTL_MAF - minor allele frequency for the QTL_SNP in each QTL study. If not available, values were obtained from the European superpopulation of 1000 Genomes phase 3</li> <li>QTL_chr - chromosome for the QTL_SNP (hg38)</li> <li>QTL_pos - genomic position in the chromosome of the QTL_SNP (hg38)</li> <li>QTL_junction - splicing junction tested in the association (for sQTLs only)</li> <li>QTL_Gene - gene name for the QTL association</li> <li>QTL_Ensembl - Ensembl gene id for the QTL_gene (GENCODE v30)</li> <li>nsnps - number of SNPs tested </li> <li>PP.H0.abf - posterior probability for H0 (no causal variant)</li> <li>PP.H1.abf - posterior probability for H1 (causal variant for trait 1 only)</li> <li>PP.H2.abf - posterior probability for H2 (causal variant for trait 2 only)</li> <li>PP.H3.abf - posterior probability for H3 (two distinct causal variants)</li> <li>PP.H4.abf - posterior probability for H4 (one common causal variant)</li> <li>cell_type - cell type of the QTL study</li> <li>SNP_distance - the absolute distance between GWAS_SNP and QTL_SNP</li> <li>LD - linkage disequilibrium between the GWAS_SNP and the QTL_SNP according to 1000 genomes phase 3 European reference panel 3 (only for PP4>0.5, -Inf otherwise)</li> </ol> <p><em>mashR_lfsr_eQTL.txt.gz - </em><strong>mashR </strong>results for <strong>eQTL</strong><em> </em>(gzip-compressed). Table columns are formatted as follows:</p> <ol> <li>ensembl_snp - Ensembl ID and the SNP prioritized by mashR (best SNP per gene)</li> <li>MFG_eur_expression_peer10.cis_qtl_nominal - local false sign rate (lfsr) of the gene-SNP pair for the MFG region</li> <li>STG_eur_expression_peer10.cis_qtl_nominal - local false sign rate (lfsr) of the gene-SNP pair for the STG region</li> <li>SVZ_eur_expression_peer5.cis_qtl_nominal - local false sign rate (lfsr) of the gene-SNP pair for the SVZ region</li> <li>THA_eur_expression_peer10.cis_qtl_nominal - local false sign rate (lfsr) of the gene-SNP pair for the THA region</li> </ol> <p><em>mashR_lfsr_eQTL.txt.gz - </em><strong>mashR </strong>results for <strong>sQTL</strong><em> </em>(gzip-compressed). Table columns are formatted as follows:</p> <ol> <li>pos_ensembl_rsnp - splicing junction coordinates, Ensembl ID, and SNP ID prioritized by mashR (best SNP per junction)</li> <li>MFG_eur_rsplicing_peer5_gene.cis_qtl_nominal - local false sign rate (lfsr) of the gene-SNP pair for the MFG region</li> <li>STG_eur_rsplicing_peer5_gene.cis_qtl_nominal - local false sign rate (lfsr) of the gene-SNP pair for the STG region</li> <li>SVZ_eur_rsplicing_peer0_gene.cis_qtl_nominal - local false sign rate (lfsr) of the gene-SNP pair for the SVZ region</li> <li>THA_eur_rsplicing_peer5_gene.cis_qtl_nominal - local false sign rate (lfsr) of the gene-SNP pair for the THA region</li> </ol> <p><em>out_mfg_stg_svz_tha.metasoft.gz - </em><strong>METASOFT</strong> results<strong> </strong>for <strong>eQTLs</strong> meta-analysis from MiGA four brain regions<em> </em>(gzip-compressed). Table columns are formatted as follows:</p> <ol> <li>RSID - Id composed by gene Ensembl and SNP ID separated by an underscore for each gene-SNP pair tested in the eQTL study</li> <li>#STUDY - number of studies included in the meta-analysis</li> <li>PVALUE_FE - <em>P</em>-value of the fixed-effects model (FE) according to METASOFT</li> <li>BETA_FE - Estimated Beta under the fixed-effects model according to METASOFT</li> <li>STD_FE - Standard error of BETA_FE</li> <li>PVALUE_RE - <em>P</em>-value of the random effects model (RE) according to METASOFT</li> <li>BETA_RE - Estimated Beta under the random-effects model (RE) according to METASOFT</li> <li>STD_RE - Standard error of BETA_RE</li> <li>PVALUE_RE2 - <em>P</em>-value of the Han and Eskin's Random Effects model (RE2) according to METASOFT</li> <li>STAT1_RE2 - RE2 statistic mean effect part</li> <li>STAT2_RE2 - RE2 statistic heterogeneity part</li> <li>PVALUE_BE - BE P-value (“NA” in all row, -binary_effects option is not used)</li> <li>I_SQUARE - I-square heterogeneity statistic</li> <li>Q - Cochran's Q statistic</li> <li>PVALUE_Q - Cochran's Q statistic's <em>P</em>-value</li> <li>TAU_SQUARE - Tau-square heterogeneity estimator of DerSimonian-Laird</li> <li>PVALUES_OF_STUDIES(Tab_delimitered) - <em>P</em>-values of each study in the respective order 1-MFG, 2-STG, 3-SVZ, 4-THA</li> <li>MVALUES_OF_STUDIES(Tab_delimitered) - M-values of each study in the respective order 1-MFG, 2-STG, 3-SVZ, 4-THA</li> </ol> <p><em>out_miga_young_mynd_fairfax.metasoft.gz - </em><strong>METASOFT</strong> results<strong> </strong>for <strong>eQTL</strong> meta-analysis from MiGA four brain regions plus microglia eQTL from Young et al. (2019), and monocytes eQTL from Navarro et al. (2020) and Fairfax et al. (2014)<em> </em>(gzip-compressed). Table columns are formatted as follows:</p> <ol> <li>RSID - Id composed by gene Ensembl and SNP ID separated by an underscore for each gene-SNP pair tested in the eQTL study</li> <li>#STUDY - number of studies included in the meta-analysis</li> <li>PVALUE_FE - <em>P</em>-value of the fixed-effects model (FE) according to METASOFT</li> <li>BETA_FE - Estimated Beta under the fixed-effects model according to METASOFT</li> <li>STD_FE - Standard error of BETA_FE</li> <li>PVALUE_RE - <em>P</em>-value of the random effects model (RE) according to METASOFT</li> <li>BETA_RE - Estimated Beta under the random-effects model (RE) according to METASOFT</li> <li>STD_RE - Standard error of BETA_RE</li> <li>PVALUE_RE2 - <em>P</em>-value of the Han and Eskin's Random Effects model (RE2) according to METASOFT</li> <li>STAT1_RE2 - RE2 statistic mean effect part</li> <li>STAT2_RE2 - RE2 statistic heterogeneity part</li> <li>PVALUE_BE - BE P-value (“NA” in all row, -binary_effects option is not used)</li> <li>I_SQUARE - I-square heterogeneity statistic</li> <li>Q - Cochran's Q statistic</li> <li>PVALUE_Q - Cochran's Q statistic's <em>P</em>-value</li> <li>TAU_SQUARE - Tau-square heterogeneity estimator of DerSimonian-Laird</li> <li>PVALUES_OF_STUDIES(Tab_delimitered) - <em>P</em>-values of each study in the respective order 1-MFG, 2-STG, 3-SVZ, 4-THA, 5-Young et al., 6-Navarro et al., 7-Fairfax et al.</li> <li>MVALUES_OF_STUDIES(Tab_delimitered) - M-values of each study in the respective order 1-MFG, 2-STG, 3-SVZ, 4-THA, 5-Young et al., 6-Navarro et al., 7-Fairfax et al.</li> </ol> <p><em>out_mfg_stg_svz_tha_sClusters.metasoft.gz - </em><strong>METASOFT</strong> results<strong> </strong>for <strong>sQTLs</strong> meta-analysis from MiGA four brain regions (gzip-compressed). Table columns are formatted as follows:</p> <ol> <li>RSID - Id composed by splicing junction coordinates, gene Ensembl ID, and SNP ID separated by underscores for each junction-SNP pair tested in the sQTL study (e.g. chr1_962047_962355_ENSG00000187961.14_1:11008:C:G)</li> <li>#STUDY - number of studies included in the meta-analysis</li> <li>PVALUE_FE - <em>P</em>-value of the fixed-effects model (FE) according to METASOFT</li> <li>BETA_FE - Estimated Beta under the fixed-effects model according to METASOFT</li> <li>STD_FE - Standard error of BETA_FE</li> <li>PVALUE_RE - <em>P</em>-value of the random effects model (RE) according to METASOFT</li> <li>BETA_RE - Estimated Beta under the random-effects model (RE) according to METASOFT</li> <li>STD_RE - Standard error of BETA_RE</li> <li>PVALUE_RE2 - <em>P</em>-value of the Han and Eskin's Random Effects model (RE2) according to METASOFT</li> <li>STAT1_RE2 - RE2 statistic mean effect part</li> <li>STAT2_RE2 - RE2 statistic heterogeneity part</li> <li>PVALUE_BE - BE P-value (“NA” in all row, -binary_effects option is not used)</li> <li>I_SQUARE - I-square heterogeneity statistic</li> <li>Q - Cochran's Q statistic</li> <li>PVALUE_Q - Cochran's Q statistic's <em>P</em>-value</li> <li>TAU_SQUARE - Tau-square heterogeneity estimator of DerSimonian-Laird</li> <li>PVALUES_OF_STUDIES(Tab_delimitered) - <em>P</em>-values of each study in the respective order 1-MFG, 2-STG, 3-SVZ, 4-THA</li> <li>MVALUES_OF_STUDIES(Tab_delimitered) - M-values of each study in the respective order 1-MFG, 2-STG, 3-SVZ, 4-THA</li> </ol> <p><strong>NOTE:</strong> The effect sizes of eQTLs and sQTL are defined as the effect of the alternative allele (ALT) relative to the reference (REF) allele in the human genome reference (GRCh38). A file containing that information for all alleles tested is available at 10.5281/zenodo.4301005</p>
Integrated field-aligned radar data and analysis results
<p>Dataset used in "A statistical survey of heat input parameters into the cusp thermosphere" J. Geophys. Res. 2017, doi:10.1002/2016JA023594.</p>
singletonpa/2019-winter-transportation-survey: Updated release of MPC-559 with analysis results
<p>This is an updated release of the MPC-559 "Investigating travel behavior and air quality in Northern Utah" (2019-winter-transportation-survey) research project. It contains additional data, scripts, and results associated with the analysis of travel behavior and activity participation outcomes.</p>
CLaMS results used for age of air analysis in the report of assessment of the ESA Earth Explorer candidate mission CAIRT
<p>Results of the Chemical Lagrangian Model of the Stratosphere (CLaMS) used for age of air analysis in the report of assessment of the ESA Earth Explorer candidate mission CAIRT. Days of results: 2011-01-01, 2011-04-01, 2011-07-01, 2011-10-01 and 2019-09-23. Included trace gases: SF6, CFC-11, CFC-12, HCFC-22, N2O and CH4. The results also include the clock tracer BA, which can be converted into the precise mean age of or air of the model environment with the attached python script 'AOA2age_years.py'.</p>
Quantitative results of the analysis of relevant components of artificial bilayered substitutes developed by tissue engineering
<p>This dataset corresponds to the quantification results carried out for artificial bilayered substitutes developed by tissue engineering and control tissues analyzed in the manuscript entitled "<span>Spatiotemporal characterization of extracellular matrix maturation in human artificial stromal-epithelial tissue substitutes</span>". Tissue engineering techniques offer new strategies to understand complex processes in a controlled and reproducible system. In this study, we generated bilayered human tissue substitutes consisting of a cellular connective tissue with a suprajacent epithelium (full-thickness stromal-epithelial substitutes or SESS), and human tissue substitutes with an epithelial layer generated on top of an acellular biomaterial (epithelial substitutes or ESS). Both types of artificial tissues were studied at sequential time periods to analyze the maturation process of the extracellular matrix (ECM) using histochemical and immunohistochemical techniques. Results showed that both models were able to exhibit a partial development of the epithelial layer. ESS cells showed active proliferation, positive expression of KRT5 and low expression of differentiation markers, whereas SESS epithelium showed higher differentiation levels, with a progressive positive expression of KRT10 and claudin, although the differentiation levels of control native tissues were not reached. Despite the typical rete-ridges and papillae of native tissues were not found, stromal cells in SESS tended to accumulate and actively synthetize ECM components such as collagens and proteoglycans in the stromal area in direct contact with the epithelium (Z1 zone), whereas these components were very scarce in ESS. Regarding the basement membrane (BM), ESS showed a partially-differentiated structure containing fibronectin-1 (FN1) and perlecan (HSPG2), although the PAS staining signal was significantly lower than control native tissues. However, SESS showed higher BM differentiation, with positive expression of FN1, HSPG2, nidogen 1 (NID1), chondroitin-6-sulfate proteoglycans (CH6S), agrin (AGRN), and collagens types IV (COL-IV) and VII (COL-VII), although this structure was negative for lumican (LUM). These results confirm the relevance of epithelial-stromal interaction for ECM development and differentiation, especially regarding BM components, and suggest the usefulness of bilayered artificial tissue substitutes to reproduce ex vivo the ECM maturation and development process of human tissues. The original data obtained for the quantitative analyses of each component are shown in this dataset.</p> <p> </p>
Wrist and Tibia/Shoe Mounted IMU Measurement Results for Gait Analysis
<p>This document describes a dataset of measurement results collected using wrist, tibia and shoe mounted inertial sensors. The main purpose of the dataset was to test signal translation algorithms converting signals registered using the wrist-worn sensor e.g. a smartwatch to signals which would be measured with a shoe or tibia - mounted device. The dataset includes tri-axial acceleration and angular velocity registered during several walks.</p> <p>More details are included in the dataset_description pdf file.</p> <p>When using the data, please consider also citing the original paper, for which it was collected:</p> <p>Kolakowski, M.; Djaja-Josko, V.; Kolakowski, J.; Cichocki, J. Wrist-to-Tibia/Shoe Inertial Measurement Results Translation Using Neural Networks. <em>Sensors</em> <strong>2024</strong>, <em>24</em>, 293. <a href="https://doi.org/10.3390/s24010293" target="_blank" rel="noopener">https://doi.org/10.3390/s24010293</a></p> <p><strong>The dataset will be gradually updated as new data are gathered.</strong></p>
Quantitative results of the analysis of novel ossicle particles used in mandible bone regeneration
<p>Dataset corresponding to the results of the characterization analysis of novel holothurian ossicle biomaterials. These biomaterials were evaluated at three levels:</p> <p>1) Ex vivo analysis to determine thr potential cytotoxic effects of these biomaterials on human fibroblasts using LIVE/DEAD and quantification of DNA released to the medium.</p> <p>2) In vivo analysis to determine the potential systemic effects of these biomaterials grafted subcutaneously in laboratory rats.</p> <p>3) Histochemical and immunohistochemical analysis to determine the potential effects of these biomaterials on mandible bone regeneration.</p> <p>These results correspond to the publication entitled "<span>EVALUATION OF HOLOTHURIAN OSSICLES AS A BIOLOGICAL BIOMATERIAL FOR MANDIBULAR BONE REGENERATION</span>".</p>
Quantitative results of the analysis of human native and bioengineered tissues corresponding to the work "Histological, histochemical and immunohistochemical characterization of NANOULCOR nanostructured fibrin-agarose human cornea substitutes generated by tissue engineering"
<p>Dataset containing the quantitative results of the histochemical and immunohistochemical analysis of the following human tissues:</p> <ul> <li>Control native cornea (CTR-C)</li> <li>Control native limbus (CTR-L)</li> <li>Artificial cornea generated by tissue engineering (HAC)</li> </ul> <p>Each tissue type was subjected to histochemical and immunohistochemical analyses and results were quantified using ImageJ software to determine average intensities and area fractions corresponding to positive staining signal for each marker.</p>
Figure 4. Results from the phylogenetic analysis using discrete data only. A in Exploring phylogenetic relationships of Pteraspidiformes heterostracans (stem-gnathostomes) using continuous and discrete characters
Figure 4. Results from the phylogenetic analysis using discrete data only. A, strict consensus of 275 most parsimonious trees with equal character weights; length 276 steps, consistency index (CI) = 0.35, retention index (RI) = 0.59, and rescaled consistency index (RC) = 0.22. B, strict consensus of four most parsimonious trees with implied character weighting (k = 3) (tree length 23.11). Psammosteidae taxa in bold.
Fig. 2. Tree resulting from implied weighting analysis using K in Pseudocetherinae (Hemiptera: Reduviidae) revisited: phylogeny and taxonomy of the lobe-headed bugs
Fig. 2. Tree resulting from implied weighting analysis using K = 12 with characters unambiguously optimized. Symmetric resampling values over 51 are represented for trees obtained with K = 3, K = 6, K = 9, and K = 12 analyses. Characters and character states are described in pp. 11–22. Specimens not to scale.
Fig. 1. Strict consensus tree resulting from equal weighting analysis. Jackknife values over 51 in Pseudocetherinae (Hemiptera: Reduviidae) revisited: phylogeny and taxonomy of the lobe-headed bugs
Fig. 1. Strict consensus tree resulting from equal weighting analysis. Jackknife values over 51 are reported for tree one of eight.
E3SM simulation results and associated python analysis scripts
<p>This archive contains E3SM Land Model simulation results associated with the <em>Journal of Advances in Modeling Earth Systems (JAMES)</em><em> </em>article titled "More Realistic Intermediate Depth Dry Firn Densification in the Energy Exascale Earth System Model (E3SM)," by Adam M. Schneider, Charles S. Zender, and Stephen F. Price. Also included in the archive are python scripts used to analyze associated data and an offline, statistical firn model.</p>
Archive of the analysis results of the microtremor data obtained from a seismic array with a radius of 0.58 m distributed to the participants of the blind prediction experiments for the ESG6 symposium
<p>This is a supplemental material of the paper "Array-size dependency of the upper limit wavelength normalized by array radius for the standard spatial autocorrelation method" by Ikuo Cho, published in Earth, Planets and Space. It consists of the analysis results of the microtremor data observed using a seismic array with a radius of 0.58 m, which were distributed to the participants of the blind prediction experiments in ESG6. It involves all analysis results and script files to draw Figure 1 of the paper. See the "Availability of data and materials" section of the paper to download the original observed data and analysis code. See the main text of the paper for the details of the analysis.</p>
Adaptive Behavior of Farmers Under Consecutive Droughts Results In More Vulnerable Farmers: A Large-Scale Agent-Based Modeling Analysis in the Bhima Basin, India
Open the record for dataset details and reuse information.
FIGURE 37. Phylogenetic results from parsimony analysis using the cranial dataset. A in A reappraisal of the cranial and mandibular osteology of the spinosaurid Irritator challengeri (Dinosauria: Theropoda)
FIGURE 37. Phylogenetic results from parsimony analysis using the cranial dataset. A, strict consensus tree of 153 MPTs retained from an equal weighting analysis (see Methods for details); B, reduced consensus tree, pruning wild card taxa from the strict consensus. Wild card taxa are highlighted with coloured boxes in A, and their possible topological positions are shown with same coloured squares in B. Important clades are labelled.
FIGURE 36. Phylogenetic results from parsimony analysis using the full dataset. A in A reappraisal of the cranial and mandibular osteology of the spinosaurid Irritator challengeri (Dinosauria: Theropoda)
FIGURE 36. Phylogenetic results from parsimony analysis using the full dataset. A, strict consensus tree of 8184 MPTs retained from an equal weighting analysis (see methods for details); B, partial reduced consensus tree, showing the clade Spinosauridae after removal of the taxon Vallibonavenatrix; C, strict consensus tree of 406 MPTs retained from an implied weighting analysis using a concavity constant of k=10 (see Methods for details). Important clades are labelled. Irritator as the main focus of our study is highlighted in bold face within the clade Spinosauridae.
Sharpness metric results and Instron method script for 'Raw Material Sharpness and Lithic Patterns: An Analysis of Holocene Susitna River Basin, Central Alaska' MPhil dissertation
<p>Data for appendix B in 'Raw Material Sharpness and Lithic Patterns: An Analysis of Holocene Susitna River Basin, Central Alaska' MPhil dissertation. This data set Includes initial and dulled sharpness metric data from the Instron® experiment for each flake. It also includes the Instron® bluehill method program script.</p>
FIGURE 6. Classification Tree results and predictions for the five fossil localities. A in What are the best modern analogs for ancient South American mammal communities? Evidence from ecological diversity analysis (EDA)
FIGURE 6. Classification Tree results and predictions for the five fossil localities. A) Results and predictions for CT1, vegetative cover. B) Results and predictions for CT2, biogeographic realm. Abbreviations: LV, La Venta; QH, Quebrada Honda; RU, Rümikon; SC, Santa Cruz; TG, Tinguiririca.
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.