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4,694 results for “data analysis”
Data and analysis from: Body mass, temperature, and depth shape the maximum intrinsic rate of population increase in sharks and rays
<p>An important challenge in ecology is to understand variation in species' maximum intrinsic rate of population increase, 𝑟<sub>𝑚𝑎𝑥</sub>, not least because 𝑟<sub>𝑚𝑎𝑥</sub> underpins our understanding of the limits of fishing, recovery potential, and ultimately extinction risk. Across many vertebrate species, terrestrial and aquatic, body mass and environmental temperature are important correlates of 𝑟<sub>𝑚𝑎𝑥</sub>. In sharks and rays, specifically, 𝑟<sub>𝑚𝑎𝑥</sub> is known be lower in larger species, but also in deep-sea ones.</p> <p>We use an information-theoretic approach that accounts for phylogenetic relatedness to evaluate the relative importance of body mass, temperature and depth on 𝑟<sub>𝑚𝑎𝑥</sub>. We show that both temperature and depth have separate effects on shark and ray 𝑟<sub>𝑚𝑎𝑥</sub> estimates, such that species living in deeper waters have lower 𝑟<sub>𝑚𝑎𝑥</sub>. Furthermore, temperature also correlates with changes in the mass scaling coefficient, suggesting that as body size increases, decreases in 𝑟<sub>𝑚𝑎𝑥</sub> are much steeper for species in warmer waters.</p> <p>These findings suggest that there are (as-yet understood) depth-related processes that limit the maximum rate at which populations can grow in deep sea sharks and rays. While the deep ocean is associated with colder temperatures, other factors that are independent of temperature, such as food availability and physiological constraints, may influence the low 𝑟<sub>𝑚𝑎𝑥</sub> observed in deep sea sharks and rays. Our study lays the foundation for predicting the intrinsic limit of fishing, recovery potential, and extinction risk species based on easily accessible environmental information such as temperature and depth, particularly for data-poor species.</p> <p>This repository contains the data and a minimum working example of the model-fitting process used for the article "Body mass, temperature, and depth shape productivity in sharks and rays", which is currently in press at <em>Ecology and Evolution</em>.</p>
Data and code – Effects of climate on salmonid productivity: A global meta-analysis across freshwater ecosystems
<p>Salmonids are of immense socio-economic importance in much of the world but are threatened by climate change. This has generated a substantial literature documenting effects of climate variation on salmonid productivity in freshwater ecosystems, but there has been no global quantitative synthesis across studies. We conducted a systematic review and meta-analysis to gain quantitative insight into key factors shaping the effects of climate on salmonid productivity, ultimately collecting 1,321 correlations from 156 studies, representing 23 species across 24 countries. Fisher's Z was used as the standardized effect size, and a series of weighted mixed-effects models were compared to identify covariates that best explained variation in effects. Patterns in climate effects were complex, and were driven by spatial (latitude, elevation), temporal (time-period, age-class), and biological (range, habitat type, anadromy) variation within and among study populations. These trends were often consistent with predictions based on salmonid thermal tolerances. Namely, warming and decreased precipitation tended to reduce productivity when high temperatures challenged upper thermal limits, while opposite patterns were common when cold temperatures limited productivity. Overall, variable climate impacts on salmonids suggest that future declines in some locations may be counterbalanced by gains in others. In particular, we suggest that future warming should (1) increase salmonid productivity at high latitudes and elevations (especially >60° and >1,500m), (2) reduce productivity in populations experiencing hotter and dryer growing season conditions, (3) favor non-native over native salmonids, and (4) impact lentic populations less negatively than lotic ones. These patterns should help conservation and management organizations identify populations most vulnerable to climate change, which can then be prioritized for protective measures. Our framework enables broad inferences about future productivity that can inform decision-making under climate change for salmonids and other taxa, but more widespread, standardized, and hypothesis-driven research is needed to expand current knowledge.</p>
Data for the analysis of aquifer-system deformation in the Doñana Natural Space (Spain) using unsupervised cloud-computed InSAR data and wavelet analysis
<p>This are the data necessary to correlate InSAR and hydrogeological information through wavelet analysis, by WaSAR Python script (Jiménez-González & Guardiola-Albert, 2022, http://doi.org/10.5281/zenodo.6334996). The structure and information about the data is the following:</p> <p>PSBAS: Processed Interferometric Synthetic Aperture Radar (InSAR) data from the European Space Agency (ESA) Sentinel-1 satellites to estimate line-of-sight (LOS) ground motion in the period 2014-2020 in the Doñana area (SW Spain). These images have been processed using the P-SBAS approach (Parallel Small BAseline Subset), which is the parallel computing solution for the SBAS processing chain at the ESA Geohazards Exploitation Platform (GEP) by CNR-IREA.</p> <p>Aggregates deformation: Former InSAR information aggregated in polygons</p> <p>Climate: rainfall and ET information in the Doñana area for the 2014-2020 period. Daily records of evapotranspiration and precipitation have been obtained from the agroclimatic stations belonging to the Junta de Andalucía (https://www.juntadeandalucia.es/agriculturaypesca/ifapa/riaweb/web/).</p> <p>Piezometry: piezometry information in Doñana area for the 2014-2020 period. Groundwater level information was provided by the piezometric networks of the Guadalquivir Hydrographic Confederation and the Geological and Mining Institute of Spain.</p> <p>Pump rates: estimated pumping rate time series in the Matalascañas touristic resort</p>
Processed data for FOXA2 analysis in TCGA KIRP and KIRC patients
<pre># Data and code to test whether FOXA2 is changed in KIRP patients with low FH ## Code https://github.com/ArianeMora/foxa2_kirp_kirc ## Datasets RNA count data were downloaded from TCGA (https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga) using scidat (https://github.com/ArianeMora/scidat) for patients with kidney cancers (rna_df.csv). ## Processing The kidney cancer patient count data were split into KIRC and KIRP, and only the tumour data was used for this analysis, see notebook FOXA2.ipynb in the code folder. Samples were split by their expression of FH in their tumour samples, with several annotations used to separate patients for completeness: 1. Low-High: Comparing the bottom 25% (< Q1) of patients by FH vs “high” FH (i.e. top 25%, > Q3): p.adj 0.00004 2. Low-Normal: Comparing the bottom 25% of patients by FH to the patients with “normal” range FH (between Q1 and Q3): p.adj 0.053 3. Outlier-High: Comparing outlier FH to “high” (i.e. top 25%): p.adj 0.067 4. Outlier-Normal: Comparing the outlier FH (Q1 – 1.5*IQR) to all “normal” FH patients: p.adj 0.169 We did the same for KIRC patients – we don’t see FOXA2 as expected 1. Comparing the bottom 25% of patients by FH vs the top 25% of patients with FH: 0.14 2. Comparing the bottom 25% of patients by FH to the patients with “normal” range FH: 0.25 3. Comparing the outlier FH to all “normal” FH patients: 0.31 4. Comparing outlier FH to “high” (i.e. top 25%): 0.32 Each of these groups were used to also perform DE analysis between the two groups, see respective RMD files in code for details. ### References If you use this work please cite TCGA: ``` Creighton, C. J., Morgan, M., Gunaratne, P. H., Wheeler, D. A., Gibbs, R. A., Gordon Robertson, A., Chu, A., Beroukhim, R., Cibulskis, K., Signoretti, S., Vandin Hsin-Ta Wu, F., Raphael, B. J., Verhaak, R. G. W., Tamboli, P., Torres-Garcia, W., Akbani, R., Weinstein, J. N., Reuter, V., Hsieh, J. J., … University of North Carolina at Chapel Hill. (2013). Comprehensive molecular characterization of clear cell renal cell carcinoma. Nature, 499(7456), Article 7456. https://doi.org/10.1038/nature12222 ``` </pre>
Meta-analysis of diurnal transcriptomics reveals strong patterns of concordance and discordance in mouse liver: processed data
<p>The accumulation of public transcriptomic timeseries data enables robust meta-analyses that were not possible until recently. To assess the consistency of biological rhythms across studies, 43 public mouse liver tissue timeseries totaling 805 RNA-seq samples were obtained and analyzed. Only the control groups of each study were included, to create comparable data. Technical factors in RNA-seq library preparation were the largest contributors to transcriptome-level differences, beyond biological or experiment-specific factors such as lighting conditions. Core clock genes were remarkably consistent in phase across all studies, while phase distributions of other periodic genes were generally less consistent. Overlap of genes identified as rhythmic across studies was generally low, with around 50% between some of the highest sample count studies. Distributions of phases of significant genes were remarkably inconsistent across studies, but genes consistently identified as rhythmic clustered near ZT0 and ZT12 in acrophase. Data was integrated across studies in a JIVE analysis, which showed that the top two components of joint within-study variation are determined by time of day. A shape-invariant model with random effects was fit to the genes to identify the underlying shape of the rhythms, consistent across all studies. This revealed the extent of asymmetric and multimodal genes.<br> <br> This supplemental file provides preprocessed RNA-seq quantifications of all reviewed datasets, as well as results of multiple analyses.</p>
Systematic analysis of alternative splicing in time course data using Spycone
<p>Spycone is available as a python package that provides systematic analysis of time course transcriptomics data. Figure 1 shows the workflow of Spycone. It uses gene or isoform expression and a biological network as an input. It employs the sum of changes of all isoforms relative abundance (total isoform usage) across time points to detect IS events. It further provides downstream analysis such as clustering by total isoform usage, gene set enrichment analysis, network enrichment, and splicing factors analysis.</p> <p>The SARS-Cov-2 infection and cancer dataset are used as an application demonstration for our Spycone tool and a simulation dataset is used for benchmark analysis. </p> <p>The rhinovirus dataset and SARS-Cov-2 infection (3 time points) for the tutorial in the documentation are included here. </p> <p>The simulated dataset from the 2 models described in the manuscript are uploaded as zen_simdata_{model}_{noise}.csv.</p> <p>A gtf file used in the splicing factor analysis, both in the manuscript and tutorial. Derived from ensembl GRCh38.99.</p>
Data: Applying stochastic and Bayesian integral projection modeling to amphibian population viability analysis
<p>Integral projection models (IPMs) can estimate the population dynamics of species for which both discrete life stages and continuous variables influence demographic rates. Stochastic IPMs for imperiled species, in turn, can facilitate population viability analyses (PVAs) to guide conservation decision-making. Biphasic amphibians are globally distributed, often highly imperiled, and ecologically well-suited to the IPM approach. Herein, we present the first stochastic size- and stage-structured IPM for a biphasic amphibian, the U.S. federally threatened California tiger salamander (<em>Ambystoma</em> <em>californiense</em>; CTS). This Bayesian model reveals that CTS population dynamics show the greatest elasticity to changes in juvenile and metamorph growth and that populations are likely to experience rapid growth at low density. We integrated this IPM with climatic drivers of CTS demography to develop a PVA and examined CTS extinction risk under the primary threats of habitat loss and climate change. The PVA indicates that long-term viability is possible with surprisingly high (20–50%) terrestrial mortality, but simultaneously identified likely minimum terrestrial buffer requirements of 600–1000 m while accounting for numerous parameter uncertainties through the Bayesian framework. These analyses underscore the value of stochastic and Bayesian IPMs for understanding both climate-dependent taxa and those with cryptic life histories (e.g., biphasic amphibians) in service of ecological discovery and biodiversity conservation. In addition to providing guidance for CTS recovery, the contributed IPM and PVA supply a framework for applying these tools to investigations of ecologically-similar species.</p>
Proteomic data sets after selecting mitochondrial proteins from the scaffold software for Ingenuity Pathway analysis (IPA Qiagen)
<p>List of fold change proteomic data sets of dFCM- 39 vs. 12Day and105 vs. 12Day, cFCM- 40 vs. 12Day and115 vs. 12Day , mouse heart 90 vs. 1 day after selecting mitochondrial proteins from the scaffold software for Ingenuity Pathway Analysis (IPA Qiagen)</p>
Training data for ChIP-seq data analysis (Galaxy Training Material): Identification of the binding sites of the Estrogen receptor
<p>The data provided here are part of a Galaxy Training Network tutorial that analyzes ChIP-seq data from a study published by Ross-Inness et al., 2012 (DOI:10.1038/nature10730) to identify the binding sites of the Estrogen receptor, a transcription factor known to be associated with different types of breast cancer.</p>
PLOS ONE – a case study of citation analysis of research papers based on the data in an open citation index (The OpenCitations Corpus)
<p>This is a dataset used in and produced by research described in article "PLOS ONE - a case study of citation analysis of research papers based on the data in an open citation index (The OpenCitations Corpus)" that is translation of the original Polish text "PLOS ONE – studium przypadku analizy cytowań prac naukowych na podstawie danych otwartego indeksu cytowań (OpenCitations Corpus)" published by EBiB bulletin (2017, No 176).</p> <p>Data were extracted, as nodes (PLOS_cited_nodes.csv) and edges (PLOS_edges.csv) files from the OpenCitations Corpus (http://opencitations.net/download) on 2017.07.25 and describe all cited papers published by PLOS ONE (nodes), and all citing relations (edges). The research was conducted using Gephi (https://gephi.org/) platform so the same source data are also avaiable as GEXF file (for "one-click" import capabilities). In addition, the same data are published in NET format (but be warned that due to this format limitations, information about the publication year of papers has been lost) used by PAJEK platform, as it is very popular tool for analysis of network data.</p> <p>Published figures have prefix names corresponding to figures captions in the original paper, where they have been thoroughly discussed. This data set contains also the additional figure not published in the article, showing most cited paper with citing chains of articles of lenght not greater than 3.<br> These pictures have much better quality than those published in the article, which allows for "drill down"/zoom-in analysis and large format printing.</p>
Data from: The State of OA: A large-scale analysis of the prevalence and impact of Open Access articles
<p>This is the raw data behind the publication: </p> <p><strong>The State of OA: A large-scale analysis of the prevalence and impact of Open Access articles.</strong></p> <p>Despite growing interest in Open Access (OA) to scholarly literature, there is an unmet need for large-scale, up-to-date, and reproducible studies assessing the prevalence and characteristics of OA. We address this need using oaDOI, an open online service that determines OA status for 67 million articles. We use three samples, each of 100,000 articles, to investigate OA in three populations: 1) all journal articles assigned a Crossref DOI, 2) recent journal articles indexed in Web of Science, and 3) articles viewed by users of Unpaywall, an open-source browser extension that lets users find OA articles using oaDOI. We estimate that at least 28% of the scholarly literature is OA (19M in total) and that this proportion is growing, driven particularly by growth in Gold and Hybrid. The most recent year analyzed (2015) also has the highest percentage of OA (45%). Because of this growth, and the fact that readers disproportionately access newer articles, we find that Unpaywall users encounter OA quite frequently: 47% of articles they view are OA. Notably, the most common mechanism for OA is not Gold, Green, or Hybrid OA, but rather an under-discussed category we dub Bronze: articles made free-to-read on the publisher website, without an explicit Open license. We also examine the citation impact of OA articles, corroborating the so-called open-access citation advantage: accounting for age and discipline, OA articles receive 18% more citations than average, an effect driven primarily by Green and Hybrid OA. We encourage further research using the free oaDOI service, as a way to inform OA policy and practice.</p>
Data and code for "Differential methylation analysis of reduced representation bisulfite sequencing experiments using edgeR"
<p>This data set provides data files and R code to accompany the article <em>Differential methylation analysis of reduced representation bisulfite sequencing experiments using edgeR</em> published by F1000Research.</p> <p>The data consists of Reduced Representation BS-seq methylation profiles of epithelial populations from the mouse mammary gland, with n=2 biological replicates for each of three cell populations.</p> <p>RNA-seq expression profiles of luminal and basal mammary epithelial populations are also provided.</p> <p>The R code undertakes an differential methylation analysis of the BS-seq profiles and demonstrates a strong negative correlation between the differential methylation and differential expression results.</p>
Data archive: Trophic structure of cold-water coral communities revealed from the analysis of tissue isotopes and fatty acid composition
<p>Data belonging to the paper: </p> <p>Dick van Oevelen, Gerard C. A. Duineveld, Marc S. S. Lavaleye, Tina Kutti and Karline Soetaert (2017) Trophic structure of cold-water coral communities revealed from the analysis of 55 tissue isotopes and fatty acid composition. Marine Biology Research, DOI: https://doi.org/10.1080/17451000.2017.1398404</p> <p>Abstract:</p> <p>The trophic structure of cold-water coral reef communities at two contrasting locations, the 800-<br> m deep Belgica Mounds (Irish margin) and 300-m deep Træna reefs (Norwegian Shelf), was<br> investigated using stable isotope (δ13C and δ15N) and fatty-acid composition analysis. A<br> broad range of specimens, with emphasis on (commercial) fish species, and organic matter<br> sources were sampled using a variety of tools. Irrespective of the environmental and<br> geographical setting, the δ15N values indicated that the food web encompasses roughly 1.5<br> to 3 trophic levels. Mobile echinoderms, i.e. sea urchins and sea stars, had highest δ15N<br> values, indicative of a high trophic position in the food web. The fraction of bacterial fatty<br> acids in reef fauna was generally low (<5%), indicating that enhanced bacterial production in<br> the water column through seafloor seepage of nutrients (‘hydraulic theory’) does not form a<br> significant energy pathway into the food web. The high fraction of algal and essential fatty<br> acids in reef fauna and fish at both locations indicates a close coupling with surface<br> productivity, but the transport mechanism depends on the hydrographic setting. At Træna,<br> Calanus copepods and euphausiids form an additional link between primary production and<br> fish, which is largely absent at Belgica Mounds. At Belgica Mounds, the reef community is<br> primarily supported by phytodetritus, as evidenced by the high contribution of algal fatty<br> acids in faunal tissue and seasonal chlorophyll a deposition and marine snow at the reef. The<br> environmental setting of cold-water coral reefs influences the structure of the associated<br> food web.</p>
Data sets for the Simulated AMPI (SAMPI) load balancing simulation workflow and Ondes3D performance analysis (Companion to CCPE - Euro-Par 2017 special issue)
<p>This package contains data sets and scripts (in an Org-mode file) related to our submission to the special Euro-Par 2017 issue of the journal "Concurrency and Computation: Practice and Experience", under the title "Performance Modeling of a Geophysics Application to Accelerate Over-decomposition Parameter Tuning through Simulation".</p>
Source data for analysis of super-enhancer interactomes v1
<p><strong>Super-enhancer interactomes from single-cells link clustering and transcription</strong></p> <p>Derek Le, Antonina Hafner, Sadhana Gaddam, Kevin Wang, Alistair Boettiger</p> <p>This Zenodo repository contains data files associated with our analysis.</p> <p>Software for processing the data is available in the associated github repository: https://github.com/BoettigerLab/SEclustering-2024</p> <p>Additional information can be found in the associated manuscript, currently in preparation -- once it is posted on BioRxiv, it will be linked here. </p> <p>This deposition currently includes<br>1) SuperEnhancerLoci.xlsx - a master data table linking the genomic sequence barcode data from the corrected tables (described below) to the corresponding super-enhancer and their genomic coordinates in mm10.<br>2) Corrected_Data_Tables_by_FOV.zip -- contains drift corrected and chromatically corrected x,y,z coordinates and cellular barcode data to track cell type and coordinate barcode data to identify genomic sequences. <br>3) Processed_Seq_Data.zip -- re-processed sequencing based data used in this study.<br>4) FOF-CT_Spot_tables.zip -- draft versions of the 4DN FOF-CT formatted data-standard spot tables. See data format description here: https://fish-omics-format.readthedocs.io/en/latest/ <br>5) Probe_Sequences.zip -- fasta files, bed files, and codebook tables for the RNA and DNA probe sequences used in this study.</p>
Supporting code and data to reproduce analysis for: Genomic signatures of past megafrugivore-mediated dispersal in Malagasy palms
<p>Seed dispersal affects gene flow and hence genetic differentiation of plant populations. During the Late Quaternary, most fruit-eating and seed-dispersing megafauna went extinct, but whether these animals have left signatures in the population genetics of their food plants, particularly those with large, 'megafaunal' fruits (i.e., > 4 cm – megafruits), remains unclear.</p> <p>Here, we assessed the population history, genetic differentiation, and recent migration among populations of four animal-dispersed palm (Arecaceae) species with large (<em>Borassus madagascariensis</em>), medium-sized (<em>Hyphaene coriacea,</em> <em>Bismarckia nobilis</em>), and small (<em>Chrysalidocarpus madagascariensis</em>) fruits on Madagascar. We integrated double-digest restriction-site-associated DNA sequencing (ddRAD) of 167 individuals from 25 populations with (past) distribution ranges for extinct and extant seed-dispersing animals (e.g., giant lemurs, elephant birds), landscape and human impact data, and applied linear mixed-effects models to explore the drivers of genetic variation in Malagasy palms.</p> <p>Palm populations that shared more megafrugivore species in the past had lower genetic differentiation than populations that shared fewer megafrugivore species. This suggests that megafrugivore-mediated seed dispersal in the past may have led to frequent gene flow among populations. In comparison, extant frugivore diversity only decreased genetic differentiation in the small-fruited palm. Furthermore, genetic differentiation decreased with landscape connectivity (i.e., environmental suitability, forest cover and river density), and human impact (i.e., road density) has decreased genetic differentiation among populations.</p> <p><em>Synthesis: </em>Our results suggest that the legacy of megafrugivores regularly achieving long dispersal distances is still reflected in the population genetics of palms that were formerly dispersed by such animals. Furthermore, low genetic differentiation was possibly maintained after the megafauna extinctions through alternative dispersal (e.g., human- or river-mediated), long generation times, and long lifespans of these megafruit palms. Our study illustrates how species interactions that happened >1000 years ago can leave imprints in population genetics.</p>
Data for publication: A pipeline for in-depth analysis of DNA virus populations by profiling the low abundant virus variants and partial genomic components
<p>Raw and processed sequence data from Oxford Nanopore and BGI short read sequencing platforms used in the publication: "A pipeline for in-depth analysis of DNA virus populations by profiling the low abundant virus variants and partial genomic components".</p>
Data and Analysis Scripts for "Diviner uncovers hundreds of novel human (and other) exons through comparative analysis of proteins"
<p>This compressed directory contains the complete set of data and analysis scripts represented in "<em>Diviner</em> uncovers novel coding regions on eukaryotic genomes using targeted homology search."</p> <p> </p>
Spectral Cluster Supertree: Analysis Data
<p>Contains all datasets used in the Spectral Cluster Supertree paper. The datasets are composed of a set of rooted model trees, and rooted source trees to predict them. Please cite the appropriate papers, depending on which of the datasets you use.</p> <p>The <code>birth_death</code> folder contains our own dataset generated for our paper (where the generation process is explained), it aims to mimic what may be seen through divide and conquer algorithms for phylogenetic reconstruction. Parameters used to simulate an alignment were simulated under parameters estimated from a sequence alignment of 3 bacterial species (Kaehler et al., 2015) - see <code>alignment</code> folder.</p> <p>The <code>SMIDGenOutgrouped</code> folder contains both the SMIDGenOG (Fleischauer and Böcker, 2016) and SMIDGenOG-5500 dataset (Fleischauer and Böcker, 2017).</p> <p>The <code>SuperTriplets</code> folder contains the SuperTriplets dataset (Ranwez et al, 2010).</p> <p> </p>
Data from: Interannual radial growth response of Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) to severe droughts: an analysis along a gradient of soil properties and rooting characteristics
<p>Dataset related to the publication: „Interannual radial growth response of Douglas-fir (<em>Pseudotsuga menziesii</em> (Mirb.) Franco) to severe droughts: an analysis along a gradient of soil properties and rooting characteristics”</p> <p>Information on the data and the tree species_site_key used can be found in the attached Read me file.</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.