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41 results for “human contact”
Data of: Imputation-free reconstructions of three-dimensional chromosome architectures in human diploid single-cells using allele-specified contacts
<p>These files are results obtained in<br><span><span><span><span>Imputation-free reconstructions of three-dimensional chromosome architectures in human diploid single-cells using allele-specified contacts</span></span></span></span><br>by Yoshito Hirata, Arisa H. Oda, Chie Motono, Masanori Shiro & Kunihiro Ohta.</p> <p>There are 33 files for the corresponding each reconstruction of three-dimensional chromosomone structures<br>for each cell.<br>There are 3D structures for 15 GM cells and 18 PBMC cells, which are obtained from the single cell Hi-C data of Tan et al. Science (2018).</p> <p>For each file, there are 6 columns:<br>The first column corresponds to the allele (0: maternal, 1: paternal)<br>The second column corresponds to the chromosome (1-22: chromosome's number, 23: X, 24: Y)<br>The third column corrsponds to the base point.<br>The fourth column, the fifth column and the sixth column correspond to x-, y-, and z-axes of our reconstruction.</p>
Human contact network analytics and COVID-19 hospital incidence in France
<p>This data set contains COVID-19 hospital incidence, temperature and human mobility and contact data recorded between 2020-03-24 and 2021-03-30 used in the paper:</p> <p>Selinger et al. 2021: Predicting COVID-19 incidence in French hospitals using human contact network analytics. 10.1016/j.ijid.2021.08.029</p> <p>See methods in the article for detailed descriptions and the data curation process.</p> <p> </p> <p><strong>1) cov_mob_tst_national.csv contains national-level data</strong><br> </p> <p>The columns comprise:</p> <p>incid_hosp: hospital admission incidence </p> <p>incid_rea: ICU admission incidence</p> <p>incid_dc: hospital death incidence </p> <p>incid_rad: incidence of those returned home</p> <p>within_departement_colocation_X%: X%-quantile of colocation probabilities with départements</p> <p>between_departement_colocation_X%: X%-quantile of colocation probabilities between départements</p> <p>fb_population_coverage_X%: X%-quantile of ratio of fb_population over census population in département</p> <p>null_links_X%: X%-quantile of null links across départements</p> <p>clustering_X%: X%-quantile of clustering coefficients across départements</p> <p>ricci_X%: X%-quantile of curvature across départements</p> <p>ricci_min_X%: X%-quantile of minimum curvature across départements</p> <p>ricci_mean_X%: X%-quantile of average curvature across départements</p> <p>ricci_max_X%: X%-quantile of maximum curvature across départements</p> <p>strength_X%: X%-quantile of network strengths across départements</p> <p>betweenness_centrality_X%: X%-quantile of betweenness_centrality scores across départements</p> <p>positive_test_ratio_weekly: ratio of weekly cumulated positive tested over weekly cumulated tests</p> <p>retail_and_recreation_percent_change_from_baseline: Google Mobility Reports</p> <p>grocery_and_pharmacy_percent_change_from_baseline: Google Mobility Reports</p> <p>parks_percent_change_from_baseline: Google Mobility Reports </p> <p>transit_stations_percent_change_from_baseline: Google Mobility Reports</p> <p>workplaces_percent_change_from_baseline: Google Mobility Reports</p> <p>residential_percent_change_from_baseline: Google Mobility Reports</p> <p>mean_temperature_X%: X% quantile of mean daily temperatures averaged over the week across départements</p> <p>min_temperature_X%: X% quantile of minimum daily temperatures averaged over the week across départements</p> <p>max_temperature_X%: X% quantile of maximum daily temperatures averaged over the week across départements</p> <p> </p> <p> </p> <p><strong>2) cov_mob_dep.csv contains département-level data</strong></p> <p>The columns comprise:</p> <p>dep: département code</p> <p>incid_hosp: hospital admission incidence </p> <p>incid_rea: ICU admission incidence</p> <p>incid_dc: hospital death incidence </p> <p>incid_rad: incidence of those returned home</p> <p>week: week (matched to colocation data recording usually on Tuesdays)</p> <p>dep_name: name of the département</p> <p>null_links: number of null links</p> <p>betweenness_centrality: betweenness centrality</p> <p>clustering: clustering coefficient</p> <p>strength: network strength</p> <p>ricci_mean: minimum curvature among all edges incident to a département</p> <p>ricci_min: mean curvature across all edges incident to a département </p> <p>ricci_X%: X%-quantile curvature among all edges incident to a département</p> <p>fb_population: number of facebook users </p> <p>facebook_colocation_within_dep: colocation probability within département</p> <p>fb_population_coverage: ratio of fb_population over census population in département</p> <p>facebook_colocation_between_dep_X%: X%-quantile of facebook colocation among all edges incident to the département</p> <p>min_temperature: minimum daily temperature averaged over the week</p> <p>max_temperature: maximum daily temperature averaged over the week</p> <p>mean_temperature: mean daily temperature averaged over the week</p> <p>incid_hosp_Y: incidence of hospital admission from Ynd most colocated département</p> <p>incid_rea_Y: incidence of ICU admission from Ynd most colocated département</p> <p>incid_dc_Y: incidence of hospital deaths from Ynd most colocated département</p> <p>incid_rad_Y: incidence of returned home from Ynd most colocated département</p> <p> </p>
Data of: Imputation-free reconstructions of three-dimensional chromosome architectures in human diploid single-cells using allele-specified contacts
Open the record for dataset details and reuse information.
Assessing changes in genomic divergence following a century of human mediated secondary contact among wild and captive-bred ducks
<p>Along with manipulating habitat, the direct release of domesticated individuals into the wild is a practice used world-wide to augment wildlife populations. We test between possible outcomes of human-mediated secondary contact using genomic techniques at both historical and contemporary time scales for two iconic duck species. First, we sequence several thousand ddRAD-seq loci for contemporary mallards (<i>Anas platyrhynchos</i>) throughout North America, and two domestic mallard-types (i.e., known game-farm mallards and feral Khaki Campbell's). We show that North American mallards may well be becoming a hybrid swarm due to interbreeding with domesticated game-farm mallards released for hunting. Next, to attain a historical perspective, we applied a bait-capture array targeting thousands of loci in century-old (1842-1915) and contemporary (2009-2010) mallard and American black duck (<i>A. rubripes</i>) specimens. We conclude that American black ducks and mallards have always been closely related, with a divergence time of ~600,000 years before present, and likely evolved through prolonged isolation followed by limited bouts of gene flow (i.e., secondary contact). They continue to maintain genetic separation, a finding that overturns decades of prior research and speculation suggesting the genetic extinction of the American black duck due to contemporary interbreeding with mallards. Thus, despite having high rates of hybridization, actual gene flow is limited between mallards and American black ducks. Conversely, our historical and contemporary data confirm that the intensive stocking of game-farm mallards during the last ~100 years has fundamentally changed the genetic integrity of North America's wild mallard population, especially in the east. It thus becomes of great interest to ask whether the iconic North American mallard is declining in the wild due to introgression of maladaptive traits from domesticated forms. Moreover, we hypothesize that differential gene flow from domestic game-farm mallards into the wild mallard population may explain the overall temporal increase in differentiation between wild black ducks and mallards, as well as the uncoupling of genetic diversity and effective population size estimates across time in our results. Finally, our findings highlight how genomic methods can recover complex population histories by capturing DNA preserved in traditional museum specimens.</p>
Machine learning reveals the diversity of human 3D chromatin contact patterns (example predictions genome wide)
<p>Example data for the paper: Machine learning reveals the diversity of human 3D chromatin contact patterns</p> <p>GitHub: https://github.com/erin-n-gilbertson/3DGenome-diversity/tree/main</p> <p>biorXiv: https://www.biorxiv.org/content/10.1101/2023.12.22.573104v1.full</p> <p>Manuscript accepted at Molecular Biology and Evolution</p> <p>Of primary interest will be the example predictions genome wide for hg38 reference, human-archaic hominin ancestor and most divergent 1KG individual per genome along with the Jupyter notebook tutorial for making your own Akita predictions given any input 1MB sequence.</p> <div> <ul> <li>bin: contains python script for and qsub array shell script for generating example predictions. These scripts can be modified to take in any fasta files as input.</li> <li>akita_predictions: contains both Akita prediction output arrays and SVG files with predicted contact maps for the hg38 reference, human-archaic hominin ancestor and most divergent 1KG individual in each of 4,873 1MB windows</li> <li>anc_window_spearman.csv: spearman correlation between each 1KG individual and the ancestor for each 1MB window. To calculate 3D divergence subtract these values from 1.</li> <li>basenji: basenji dir from their github, necessary in the directory to run predictions - https://github.com/calico/basenji/tree/master</li> <li>genomes: fasta genomes for hg38 reference and human-archaic hominin ancestor used to make akita predictions</li> <li>divergent_windows: variants and expected divergence distributions for 392 more divergent than expected windows. Defined in the manuscript as windows where 3D divergence between 1KG indiivudals and the ancestor is greater than what would be expected based on sequence divergence. See manuscript Fig. S9 for more details. </li> <li>windows.txt: 4,873 1MB genomic windows with 100% coverage in hg38 used for Akita predictions</li> <li>making_examples.ipynb: jupyter notebook with tutorial instructions for making Akita predictions on any human genome sequence.</li> </ul> <br><br></div>
Native American use of cetaceans in pre-contact Oregon: Biomolecular and taphonomic analyses illuminate human-cetacean relationships: MALDI-TOF data
<p><span>This study characterizes how Native Americans living on the Oregon coast used whales and small cetaceans prior to European contact. We present an original analysis of a large subsample of archaeological cetacean remains from the Palmrose (35CLT47) site and new identifications from the previously analyzed Par-Tee (35CLT20) and Tahkenitch Landing (35DO130) sites. Using zooarchaeological and biomolecular analyses we report species presence and modification patterns to characterize use. Grays (<em>Eschrichtius</em> <em>robustus</em>) and humpbacks (<em>Megaptera</em> <em>novaeangliae</em>) were the most commonly identified whale species and a preferred source of food, oil, bone for tool manufacture, and possibly ligaments for sinew. Dolphins and porpoises, especially harbor porpoise (<em>Phocoena</em> <em>phocoena</em>), were a source of food and possibly bone for tool manufacture. While opportunistic hunting may have occurred, the presence of species such as blue (<em>Balaenoptera</em> <em>musculus</em>) and Cuvier's beaked (<em>Ziphius</em> <em>cavirostris</em>) whales suggest collection of beached animals was an important acquisition strategy. Our study demonstrates the value of biomolecular analyses for improved species identifications/understanding of species richness, and the value of zooarchaeological analysis to fully understand dietary and cultural contributions of cetaceans to precontact lifeways on the Oregon coast.</span></p>
Human-centered Design and Communities of Practice to Improve Home-based Tuberculosis Contact Investigation in Uganda
ClinicalTrials.gov study NCT05640648. IPD Sharing: YES. Countries: 1. Publications: 2.
Cross-species analysis of genetic architecture and polygenic risk scores for non-contact ACL rupture in dogs and humans
Open the record for dataset details and reuse information.
Assessing changes in genomic divergence following a century of human mediated secondary contact among wild and captive-bred ducks
Open the record for dataset details and reuse information.
Native American use of cetaceans in pre-contact Oregon: Biomolecular and taphonomic analyses illuminate human-cetacean relationships: MALDI-TOF data
Open the record for dataset details and reuse information.
United States, 1990 - 2015, human cases of rabies resulting from unprotected physical contact with a bat (other than visible bites and scratches)
<p>A case series of human cases of rabies resulting from unprotected physical contact with a bat (other than visible bites and scratches) verified as being caused by a bat RABV variant</p>
Activity-by-Contact model of enhancer specificity from thousands of CRISPR perturbations [RNA-Seq human]
GEO Series GSE118843. Homo sapiens. 24 samples. Type: Expression profiling by high throughput sequencing.
Satellite glial contact enhances differentiation and maturation of human induced sensory neurons
GEO Series GSE272868. Rattus norvegicus; Homo sapiens. 14 samples. Type: Expression profiling by high throughput sequencing.
Hypoxia and loss of GCM1 expression prevents differentiation and contact inhibition in human trophoblast stem cells [RNA-Seq 2]
GEO Series GSE276594. Homo sapiens. 45 samples. Type: Expression profiling by high throughput sequencing.
Genome-wide contacts of rDNA units detected by 4C procedure in human genome [hESM01]
GEO Series GSE175909. Homo sapiens. 2 samples. Type: Other.
Genome-wide inter-chromosomal contacts of rDNA units detected by 4C procedure in human Mel Z melanoma cells.
GEO Series GSE295545. Homo sapiens. 4 samples. Type: Other.
Genome-wide contacts of rDNA units detected by 4C procedure in human genome [old]
GEO Series GSE121413. Homo sapiens. 2 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Association between Activated Loci of HML-2 Primate-Specific Endogenous Retrovirus and Newly Formed Chromatin Contacts in Human Primordial Germ Cell-like Cells
GEO Series GSE284598. Homo sapiens. 6 samples. Type: Other.
Genome-wide contacts of rDNA units detected by 4C procedure in human genome [old.hs]
GEO Series GSE121417. Homo sapiens. 2 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Multi-contact 3C data reveal that the human genome is largely unentangled
GEO Series GSE146945. Homo sapiens. 2 samples. Type: Other.
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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.