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.
14,185
datasets available to search
ShareScore release 0.9.0
Dataset results
14,185 results for “phylogeny.”
Undinarchaeota illuminate DPANN phylogeny and the impact of gene transfer on archaeal evolution
<p><strong>General Description </strong></p> <p>Repository with all analyses described our paper: <a href="https://www.nature.com/articles/s41467-020-17408-w">Undinarchaeota illuminate DPANN phylogeny and the impact of gene transfer on archaeal evolution</a>.</p> <p>If you find this work useful for your own analyses, please cite this work.</p> <p> </p> <p><strong>Abstract</strong></p> <p>The evolution and diversification of Archaea is central to the history of life on Earth. Cultivation-independent approaches have revealed the existence of the DPANN archaea: a radiation of organisms with small cell and genome sizes. Currently, the placement of the various DPANN lineages and in turn the early evolution of metabolism and symbiosis are debated. Here, we reconstructed genomes of a thus far uncharacterized archaeal phylum-level lineage UAP2 (<em>Candidatus</em> Undinarchaeota). Comparative genomics revealed that members of the Undinarchaeota have small estimated genome sizes and, while potentially being able to conserve energy through fermentation, likely depend on partner organisms for the acquisition of vitamins, amino acids and other metabolites. In contrast to previous indications, our phylogenomic analyses robustly placed the Undinarchaeota as independent lineage between two major and highly supported clans of ‘DPANN’. Furthermore, our work suggests that DPANN archaea have exchanged core genes with their hosts by horizontal gene transfer, adding to the difficulty of placing DPANN in the tree of life (ToL). In several cases, this pattern is sufficiently dominant that known symbiont-host clades can be identified by inferring routes of HGT across the ToL. Together, our findings provide crucial insights into the origins and evolution of DPANN archaea and their hosts.</p> <p><strong>The annotation workflow for archaeal/bacterial genomes that was used for this paper is also available on github (<a href="https://github.com/ndombrowski/Genome_annotations">here</a>) and an updated version that includes the COG search is available on: </strong><a href="https://github.com/ndombrowski/Annotation_worfklow">https://github.com/ndombrowski/Annotation_workflow</a></p> <p> </p> <p><strong>Repository Contents</strong></p> <p><strong>1_Genome_files.tar.gz</strong> includes all Undinarchaeota (original name UAP2) metagenome-assembled genomes (MAGs). This includes: </p> <ol> <li>The original contigs for each UAP2 MAG (fna files)</li> <li>The prokka output for each UAP2 MAG (faa files)</li> <li>A concatenated file of all proteins from each UAP2 MAG and all archaeal reference genomes (364 genomes in total). This folder also includes a list of archaeal genomes investigated.</li> </ol> <p><strong>2_Phylogenies.tar.gz</strong> includes all files for the phylogenetic analyses. This includes the following folders:</p> <p>1. Files for the concatenated species trees for different taxa sets. These files are related to the following parts of the manuscript: Supplementary Table 6; Figure 1 and Supplementary Figures S8-S58. The folder includes the following:</p> <ul> <li>Folder '1_unaligned_sequences' includes individual protein sequences extract from the different taxa sets.</li> <li>Folder '2_alignments' includes the alignment files generated by MAFFT.</li> <li>Folder '3_alignments_trimmed' includes the alignments trimmed with BMGE.</li> <li>Folder '4_phylogenies' includes the IQ-TREE output for all phylogenies as well as color-annotation file for figtree. Additionally files rooted with minimal ancestor deviation (MAD) rooting (*.rooted) are provided. Note, that for the final figures the *treefile_renamed (i.e. the iqtree file with the full taxa string) were artificially rooted using the DPANN archaea. The numbering corresponds to Supplementary Table S6 of the main manuscript.</li> <li>Folder ' 5_pdfs' includes the PDFs for each tree</li> </ul> <p>2. Files for single gene trees that includes:</p> <ul> <li>The folder '1_arcogs' includes the unaligned proteins, alignments, trimmed alignments, trees and pdfs for the single gene trees based on the arCOG identifiers. The arCOGs were extract from 12 UAP2 MAGs + 352 archaeal + 3020 bacterial + 100 eukaryotic genomes. ArCOGs were only considered if they occurred in at least 3 UAP2 genomes. Notice, these files were used to investigate UAP2 for HGT events and correspond to the following parts of the manuscript: Figure 4 and Supplementary Tables 4, 5, 20-22. Additionally, the folder 0_parsing includes some information on how to generate count tables for each marker gene.</li> <li>The folder '151_markers' including the proteins, alignments, trimmed alignments, trees and pdfs for evaluating the 151 marker set used for the concatenated species tree. Files were provided for the 127 and 364 taxa set. These files were used as a basis for the concatenated species trees that were used to generated Supplementary Figures S8-S58. Additionally, the trees were used for ranking marker proteins and generating Supplementary Tables 4-5. For the 364 taxa set, the folder also included a subfolder 0_parsing that provides scripts to investigate some statistics for each marker protein, including the average protein length, average alignment length and average bootstrap support.</li> <li>The folder '3_other_individual_trees' includes the proteins, alignments and phylogenies for the 16S_23S, RubisCO and primase analyses. The data was used to generate the following parts of the manuscript: Supplementary Table 11, Supplementary Figures 3-5, 57 and 59.</li> </ul> <p><strong>3_Scripts.tar.gz</strong> includes all files for the phylogenetic analyses. This includes the following folders:</p> <p>1. The files for the main workflow for the annotations and phylogenies.</p> <ul> <li>This folder includes the workflow to generate annotations for archaeal genomes as well as an example script that was used to generate phylogenies. These analyses were typically run on a in-house bioinformatics cluster with 4x Xeon Gold 6140 2.3 GHz processors using bash, python and perl. The used system runs a Linux operating system, Red Hat Enterprise 7.5.</li> </ul> <p>2. A folder providing any required dependencies that include:</p> <ul> <li>any python or perl scripts that were used during this study and/or that are mentioned in the methods section</li> <li>Databases used for the annotations, esp. if these were slightly modified. Notice, changes typically include parsing of the mapping files or modifications of the sequence headers for easier parsing.</li> <li>mapping files needed to link the genome accession ids to the taxonomy string as well as lists of protein IDs used for different phylogenies (i.e. 14 + 48 arCOGs used for protein phylogenies)</li> </ul> <p>3. R scripts (including all needed input files) used to: </p> <ul> <li>generate tables and figures for the annotations, i.e. Figure 2 and 3 and Supplementary Tables 7, 8, 9, 12, 13-15 and Supplementary Figures 60, 62-64 . The input folder includes the raw output from the annotation workflow and includes annotations for the 12 UAP2 MAGs as well as 352 archaeal reference genomes.</li> <li>generate tables and figures for the HGT analyses, i.e. Figure 4 and Supplementary Tables S20-22 Here, proteins based on arCOGs were extracted from 364 archaeal, 3020 bacterial and 98 eukaryotic genomes and used to generate single protein phylogenies. The resulting trees were used to investigate horizontal gene transfer events and the necessary scripts are provided in this folder.</li> <li>generate tables and figures for the amino acid identify (AAI) comparisons, i.e. Supplementary Table S3 and Supplementary Figure S2. </li> <li>rank the marker genes for concatenated species trees for the 127 and 364 taxa set. These were used to generate Supplementary Tables S4 and S5.</li> </ul> <p><strong>General comment:</strong></p> <p>In contrast to the previous version, this datasets includes some small additional scripts generated during the revision process of the corresponding manuscript.</p> <p> </p>
Phylogeny of "Philoceanus complex" seabird lice (Phthiraptera: Ischnocera) inferred from mitochondrial DNA sequences
<p>Data from "Phylogeny of “<em>Philoceanus </em>complex” seabird lice (Phthiraptera: Ischnocera) inferred from mitochondrial DNA sequences". See the file index.html for details. Data includes NEXUS files for sequences, tree files output by MrBayes and PAUP, and host-parasite association files for TreeMap.</p>
A multi-locus phylogeny for the Diamesinae (Chironomidae: Diptera) provides new insights into evolution of an amphitropical clade
<p>Aligned FASTA files for each locus, Concatinated Dataset, Input files for MrBayes, IqTree2, PartitionFinder and RASP. Ready trees after MrBayes and BEAST. </p>
Dataset: Systematics of the color-polymorphic spider genus Cybaeolus, with comments on the phylogeny of the family Hahniidae (Araneae)
<p>Phylogenetic analysis of the spiders of the genus Cybaeulus, with outgroups in the marronoid clade. Data from six DNA markers, analyzed with maximum likelihood and parsimony.</p> <p><br>PHYLOGENETIC ANALYSIS</p> <p>We obtained sequences from 26 samples of the three known species of Cybaeolus, and of five additional species of Hahniidae. To these, we added legacy sequences of Cybaeolus and of other genera of Hahniidae, as well as representatives of the remaining families in the marronoid clade. For the new sequences, the extraction and amplification of DNA was made in the Laboratory of Molecular Tools at Museo Argentino de Ciencias Naturales (MACN), from tissues preserved in absolute alcohol at -18ºC. We targeted the markers histone H3 (H3), cytochrome oxidase subunit I (CO1), 28S ribosomal RNA (28S) and 16S ribosomal RNA (16S), previously used to estimate relationships of marronoid spiders (Wheeler et al., 2017). Details of extraction, primers and PCR protocols are the same as in Magalhaes & Ramírez (2022). Sequencing was outsourced to Macrogen Inc., South Korea. The resulting chromatograms were analyzed individually to detect contaminated sequences or ambiguous portions. In addition to these sequences obtained in the laboratory, we combined our data with additional sequences from previous work (Wheeler et al., 2017; Rivera-Quiroz et al., 2020), using the markers mentioned above plus 12S ribosomal RNA (12S) and 18S ribosomal RNA (18S). For the CO1 marker, additional sequences obtained by the Arachnology Division at MACN and deposited in the BOLDSYSTEMS platform (https://www.boldsystems.org/) were also used. Sequences were aligned with MAFFT Online v.7.463 (Katoh & Standley, 2013), using the L-INS-I algorithm. See Table 1 for list of vouchers and sequence identifiers.</p> <p>Maximum likelihood<br>For the maximum likelihood analyses we used the program IQ-TREE 2.2.0 (Minh et al., 2020), partitioning the data by marker, and selecting the best combination of partitions and evolution models by Bayesian information criterion (best fitting models were TPM2+I+G4 for H3, GTR+F+I+G4 for 18S, GTR+F+I+G4 for 16S and 12S together, GTR+F+I+G4 for CO1, and GTR+F+I+G4 for 28S). Since the relationships of outgroup taxa in the resulting trees were slightly different to that found in recent phylogenomic studies, we used the study of Gorneau et al. (2023) based on ultraconserved elements as a backbone topology to constrain our tree search, considering only the taxa in common with our analysis (see supplementary Fig. S1); this means that all the rest of the taxa are free to move anywhere during tree search. Support for groups (branches) was estimated by 1000 cycles of ultrafast bootstrapping. Ten independent runs were performed; of those, six converged into nearly identical log likelihood values (-57417.7725 to -57417.9604) and identical topologies; the tree with top-ranking log likelihood is presented in Results, after collapsing branches with bootstrap below 0.5. To estimate the support of an alternative topology with Cybaeolus as sister to the rest of the hahniids, we used TNT 1.6 (Goloboff & Morales, 2023) to modify the optimal tree placing Cybaeolus in such position, and asked for the frequency of the branch of interest (all hahniids except Cybaeolus) in the 1000 bootstrapped trees previously saved by IQTREE.<br>Ancestral character states for the arrangement of spinnerets (grouped; separated in a transversal line) were estimated by maximum likelihood on the optimal tree, using the R packages phytools and ape, under the models ER and ARD, and the best fitting model selected by the Akaike information criterion. </p> <p>Parsimony<br>For the parsimony analyses we used TNT 1.6. For the equal weights analysis, a heuristic search was made using a driven search with the default parameters of the “new technologies”, aiming for 10 independent hits to minimum length. The resulting trees were then submitted to an additional round of tree-bisection reconnection (TBR) branch swapping. These results were compared to a simpler search strategy of 300 random addition sequences, each followed by TBR, which produced 20 hits to minimal length. As both strategies reached the same trees with multiple independent hits, it is likely that the optimal trees were found. Finally, the strict consensus of all the optimal trees was obtained, and on this consensus the support values were calculated by means of 1000 bootstrap pseudoreplicates. </p>
Enhanced genome annotation strategy provides novel insights on the phylogeny of 'Flaviviridae': Supplementary material
<p>SUPPLEMENTARY MATERIAL</p> <p><strong>Index</strong></p> <ul> <li> <p>Table S1 (tableS1.csv): genomic data.</p> </li> <li> <p>Table S2 (tableS2.csv): character categorization for selected nodes.</p> </li> <li> <p>Table S3 (tableS3.csv): programs and parameters.</p> </li> <li> <p>Table S4 (tableS4.csv): annotation efficiency.</p> </li> <li> <p>File S1 (fileS1.gff): gene annotation.</p> </li> <li> <p>File S2 (fileS2.xml): configuration file for BEAST 2 (configuration.xml).</p> </li> <li> <p>Figure S1 (figureS1.pdf): dendrogram depicting the hierarchical clusters of trees based on match-split distances.</p> </li> <li> <p>Figure S2 (figureS2.pdf): full version of the working phylogenetic hypothesis (tree No. 0 in table 1).</p> </li> </ul> <p><strong>Figure captions</strong></p> <ul> <li>Figure S1: A dendrogram depicting the hierarchical clusters of trees based on match-split distances. Outgroup sequences (<em>Hepacivirus</em>, <em>Pegivirus</em>, and <em>Pestivirus</em>) were removed to guarantee the compared tree topologies would have the same terminals. Tree numbers correspond to those in table 1 of the manuscript. I. No outgroup sequences; some matrices were partitioned. II. Outgroup sequences and partitioned matrices. *This tree was produced without outgroup sequences.</li> <li>Figure S2: Full version of the working phylogenetic hypothesis (tree No. 0 in table 1). Branch lengths represent an estimation of the number of substitutions per site. Node labels indicate SH-aLRT support / ultrafast bootstrap (only shown if one of there is a value below 90%). Clade names correlate to the character categorization analysis (see table S2). Branch labels represent the four genera: I = <em>Pestivirus</em>; II = <em>Pegivirus</em>; III = <em>Hepacivirus</em>; IV = <em>Flavivirus</em>. * The Ecuador Paraiso Escondido virus (EPEV) was isolated from sand flies (<em>Psathyromyia abonnenci</em>). The EPEV was the first sand fly-borne <em>Flavivirus</em> identified in the New World.</li> </ul> <p><strong>Manuscript title</strong></p> <p>FLAVi: an enhanced annotator for viral genomes of <em>Flaviviridae</em>.</p> <p><strong>Authors</strong></p> <ul> <li> <p>de Bernardi Schneider, Adriano. University of California San Diego. ORCID: 0000-0001-7487-266X.</p> </li> <li> <p>Jacob Machado, Denis. University of North Carolina at Charlotte. ORCID: 0000-0001-9858-4515. Corresponding author.</p> </li> <li> <p>Guirales, Sayal. University of North Carolina at Charlotte.</p> </li> <li> <p>Janies, Daniel. University of North Carolina at Charlotte.</p> </li> </ul> <p><em>First author</em>: Adriano de Bernardi Schneider and Denis Jacob Machado have contributed equally to the manuscript.</p> <p><strong>Contact information</strong></p> <ul> <li> <p>Corresponding author: Denis Jacob Machado, Ph.D.</p> </li> </ul> <ul> <li> <p>OrcID: 0000-0001-9858-4515.</p> </li> </ul> <ul> <li> <p>Email: dmachado [at] uncc.edu.</p> </li> </ul> <p><strong>Other additional material</strong></p> <ul> <li>In addition to the material listed above, all 31 tree topologies and 15 alignment matrices discussed in this manuscript will are available in TreeBASE (<a href="http://purl.org/phylo/treebase/phylows/study/TB2:S24096">http://purl.org/phylo/treebase/phylows/study/TB2:S24096</a>) after the publication of the manuscript.</li> <li>The FLAVi pipeline and all the original scripts are available at GitLab (<a href="https://gitlab.com/MachadoDJ/FLAVi">https://gitlab.com/MachadoDJ/FLAVi</a>).</li> <li>The web application can be accessed at <a href="http://flavi-web.com">http://flavi-web.com</a>.</li> </ul>
Inferring the mammal tree: Species-level sets of phylogenies for questions in ecology, evolution, and conservation
<p>Big, time-scaled phylogenies are fundamental to connecting evolutionary processes to modern biodiversity patterns. Yet inferring reliable phylogenetic trees for thousands of species involves numerous trade-offs that have limited their utility to comparative biologists. To establish a robust evolutionary timescale for all ~6000 living species of mammals, we developed credible sets of trees that capture root-to-tip uncertainty in topology and divergence times. Our 'backbone-and-patch' approach to tree-building applies a newly assembled 31-gene supermatrix to two levels of Bayesian inference: (i) backbone relationships and ages among major lineages, using fossil node- or tip-dating; and (ii) species-level 'patch' phylogenies with non-overlapping in-groups that each correspond to one representative lineage in the backbone. Species unsampled for DNA are either excluded ('DNA-only' trees) or imputed within taxonomic constraints using branch lengths drawn from local birth-death models ('completed' trees). Joining time-scaled patches to backbones results in species-level trees of extant Mammalia with all branches estimated under the same modeling framework, thereby facilitating rate comparisons among lineages as disparate as marsupials and placentals. We compare our phylogenetic trees to previous estimates of mammal-wide phylogeny and divergence times, finding that (i) node ages are broadly concordant among studies, and (ii) recent (tip-level) rates of speciation are estimated more accurately in our study than in previous 'supertree' approaches where unresolved nodes led to branch length artifacts. Credible sets of mammalian phylogenetic history are now available for download at <a href="http://vertlife.org/phylosubsets">http://vertlife.org/phylosubsets</a>, enabling investigations of long-standing questions in comparative biology.</p>
Phlorest phylogeny derived from Walker & Ribeiro 2011 'Bayesian phylogeography of the Arawak expansion in lowland South America'
<p>Cite the source of the dataset as:</p> <blockquote> <p>Walker, R. S., & Ribeiro, L. A. (2011). Bayesian phylogeography of the Arawak expansion in lowland South America. Proceedings of the Royal Society B: Biological Sciences, 278(1718), 2562–2567.</p> </blockquote>
Phlorest phylogeny derived from Sagart et al. 2019 'Dated language phylogenies shed light on the ancestry of Sino-Tibetan'
<p>Cite the source of the dataset as:</p> <blockquote> <p>Sagart L, Jacques G, Lai Y, Ryder RJ, Thouzeau V, Greenhill SJ, List J- M. 2019 Dated language phylogenies shed light on the ancestry of Sino-Tibetan. Proceedings of the National Academy of Sciences, 201817972.</p> </blockquote>
Phlorest phylogeny derived from Zhang et al 2019 'Phylogenetic evidence for Sino-Tibetan origin in northern China in the Late Neolithic'
<p>Cite the source of the dataset as:</p> <blockquote> <p>Zhang M, Yan S, Pan W, & Jin L. 2019. Phylogenetic evidence for Sino-Tibetan origin in northern China in the Late Neolithic. Nature, 569, 112–115.</p> </blockquote>
Phlorest phylogeny derived from Lee & Hasegawa 2013 'Evolution of the Ainu Language in Space and Time'
<p>Cite the source of the dataset as:</p> <blockquote> <p>Lee S, Hasegawa T (2013) Evolution of the Ainu Language in Space and Time. PLoS ONE 8(4): e62243. doi: 10.1371/journal.pone.0062243</p> </blockquote>
Phlorest phylogeny derived from Lee 2015 'A Sketch of Language History in the Korean Peninsula'
<p>Cite the source of the dataset as:</p> <blockquote> <p>Lee S (2015) A Sketch of Language History in the Korean Peninsula. PLoS ONE 10(5): e0128448. doi:10.1371/journal.pone.0128448</p> </blockquote>
Phlorest phylogeny derived from Kolipakam et al. 2018 'A Bayesian phylogenetic study of the Dravidian language family'
<p>Cite the source of the dataset as:</p> <blockquote> <p>Kolipakam V, Jordan FM, Dunn M, Greenhill SJ, Bouckaert R, Gray RD & Verkerk A. 2018. A Bayesian phylogenetic study of the Dravidian language family. R. Soc. Open Sci. 5: 171504.</p> </blockquote>
Phlorest phylogeny derived from Gray et al. 2009 'Language phylogenies reveal expansion pulses and pauses in Pacific settlement'
<p>Cite the source of the dataset as:</p> <blockquote> <p>Gray RD, Drummond AJ, & Greenhill SJ 2009. Language phylogenies reveal expansion pulses and pauses in Pacific settlement. Science, 323(5913), 479-483.</p> </blockquote>
Phlorest phylogeny derived from Chang et al. 2015 'Ancestry-constrained phylogenetic analysis supports the Indo-European steppe hypothesis'
<p>Cite the source of the dataset as:</p> <blockquote> <p>Chang W, Cathcart C, Hall D, & Garrett A. 2015. Ancestry-constrained phylogenetic analysis supports the Indo-European steppe hypothesis. Language, 91(1):194-244.</p> </blockquote>
Phlorest phylogeny derived from Bowern & Atkinson 2012 'Computational phylogenetics and the internal structure of Pama-Nyungan'
<p>Cite the source of the dataset as:</p> <blockquote> <p>Bowern C & Atkinson QD. 2012. Computational phylogenetics and the internal structure of Pama-Nyungan. Language, 88(4), 817-845.</p> </blockquote>
Phlorest phylogeny derived from Bouckaert et al. 2012 'Mapping the Origins and Expansion of the Indo-European Language Family'
<p>Cite the source of the dataset as:</p> <blockquote> <p>Bouckaert RR, Lemey P, Dunn M, Greenhill SJ, Alekseyenko AV, Drummond AJ, Gray RD, Suchard MA & Atkinson QD. 2012. Mapping the Origins and Expansion of the Indo-European Language Family. Science, 337(6097), 957-960.</p> </blockquote>
Phlorest phylogeny derived from Grollemund et al. 2015 'Bantu expansion shows habitat alters the route and pace of human dispersals'
<p>Cite the source of the dataset as:</p> <blockquote> <p>Grollemund R, Branford S, Bostoen K, Meade A, Venditti C & Pagel M. 2015. Bantu expansion shows habitat alters the route and pace of human dispersals. Proceedings of the National Academy of Sciences of the USA, 112(43), 13296-13301.</p> </blockquote>
Phlorest phylogeny derived from Chacon & List 2015 'Improved computational models of sound change shed light on the history of the Tukanoan languages'
<p>Cite the source of the dataset as:</p> <blockquote> <p>Chacon TC, List J-M (2015) Improved computational models of sound change shed light on the history of the Tukanoan languages. Journal of Language Relationship, 3:177–203.</p> </blockquote>
Phlorest phylogeny derived from Birchall et al. 2016 'A combined comparative and phylogenetic analysis of the Chapacuran language family'
<p>Cite the source of the dataset as:</p> <blockquote> <p>Birchall, Joshua, Michael Dunn, and Simon J. Greenhill. 2016. A combined comparative and phylogenetic analysis of the Chapacuran language family. International Journal of American Linguistics 82 (3): 255–84. doi: 10.1086/687383</p> </blockquote>
Phlorest phylogeny derived from Hruschka et al. 2015 'Detecting regular sound changes in linguistics as events of concerted evolution'
<p>Cite the source of the dataset as:</p> <blockquote> <p>Hruschka, D. J., Branford, S., Smith, E. D., Wilkins, J., Meade, A., Pagel, M., & Bhattacharya, T. (2015). Detecting regular sound changes in linguistics as events of concerted evolution. Current Biology, 25(1), 1-9.</p> </blockquote>
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.