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1,026 results for “Linked data”
Summary level-data accompanying "A functional locus at 8q21.13 associated to FABP4 levels and causally links coronary artery disease and type 2 diabetes"
<p><strong>Introduction</strong></p> <p>These are the <em>Summary Level-data</em> as presented in:</p> <p>"A functional locus at 8q21.13 associated to FABP4 levels and causally links coronary artery disease and type 2 diabetes". <em>Unpublished</em>. (tentative title)</p> <p>If you use these data please cite this DOI or the (pre)print when available. When you have any questions or comments regarding this study or these files, please contact me via:</p> <p><strong>Sander W. van der Laan, PhD</strong> | <em>Central Diagnostics Laboratory, Division Laboratory, Pharmacy and Biomedical genetics, Circulatory Health Program, University Medical Center Utrecht, Utrecht University</em> | s.w.vanderlaan-2 [at] umcutrecht [dot] nl or s.w.vanderlaan [at] gmail [dot] com | @swvanderlaan</p> <p> </p> <p><strong>Files and description</strong></p> <p>There are three files available:</p> <ol> <li>meta.GWAS.FABP4.1Gp1.EUR.MODEL1.* - Gzipped file containing all the (unfiltered) meta-analysis results for model 1 (FABP4 ~ SNP + age + sex + PC1-10 + study specific covariates). <ul> <li>Discovery dataset ends with: "summaryQC.ELISAonly.txt.gz"</li> <li>Replication dataset ends with: "summaryQC.OLINKonly.txt.gz"</li> <li>Combined dataset ends with: "summaryQC.txt.gz"</li> </ul> </li> <li>meta.GWAS.FABP4.1Gp1.EUR.MODEL2.* - Gzipped file containing all the (unfiltered) meta-analysis results for model 2 (FABP4 ~ SNP + age + sex + PC1-10 + study specific covariates + BMI). <ul> <li>Discovery dataset ends with: "summaryQC.ELISAonly.txt.gz"</li> <li>Replication dataset ends with: "summaryQC.OLINKonly.txt.gz"</li> <li>Combined dataset ends with: "summaryQC.txt.gz"</li> </ul> </li> <li>meta.GWAS.FABP4.1Gp1.EUR.MODEL3.* - Gzipped file containing all the (unfiltered) meta-analysis results for model 3 (FABP4 ~ SNP + age + sex + PC1-10 + study specific covariates + BMI + eGFR). <ul> <li>Discovery dataset ends with: "summaryQC.ELISAonly.txt.gz"</li> <li>Replication dataset ends with: "summaryQC.OLINKonly.txt.gz"</li> <li>Combined dataset ends with: "summaryQC.txt.gz"</li> </ul> </li> </ol> <p>All these files have the same lay-out and are gzipped. The reference used for meta-analysis of GWAS was 1000G phase 1, version 3 (so called 'ALL.wgs.integrated_phase1_v3.20101123.snps_indels_sv.sites'-panel) using data from the EUR populations. For a more detailed explanation of these columns and the reason to include them, please refer to <a href="https://doi.org/10.1093/hmg/ddn288">De Bakker <em>et al.</em> Hum Mol Genet 2008</a>. </p> <ul> <li><em>VARIANTID</em> - variantID as represented in 1000G phase 1, version 3.</li> <li><em>CHR</em> - chromosome numbers [1-22 and X, Y, MT].</li> <li><em>POS</em> - base pair position.</li> <li><em>MINOR</em> - minor allele as present in 1000G.</li> <li><em>MAJOR</em> - major allele as present in 1000G.</li> <li><em>MAF</em> - minor allele frequency as present in 1000G.</li> <li><em>CODEDALLELE</em> - coded allele, <em>i.e.</em> the effect allele, as represented (and harmonized) across cohorts. Note that this is not necessarily the minor allele!</li> <li><em>OTHERALLELE</em> - the other allele, <em>i.e.</em> the non-effect allele.</li> <li><em>CAF</em> - coded allele frequency, <em>i.e.</em> the effect allele frequency. Note that this is not necessarily the minor allele frequency!</li> <li><em>N_EFF</em> - the effective sample size corrected for the imputation quality.</li> <li><em>Z_SQRTN</em> - Z-score of the effective sample-size-weighted meta-analysis.</li> <li><em>P_SQRTN</em> - P-value of the effective sample-size-weighted meta-analysis.</li> <li><em>BETA_FIXED</em> - beta from the fixed-effects model.</li> <li><em>SE_FIXED</em> - standard error from the fixed-effects model.</li> <li><em>Z_FIXED</em> - z-score from the fixed-effects model.</li> <li><em>P_FIXED</em> - P-value from the fixed-effects model.</li> <li><em>BETA_LOWER_FIXED</em> - 95% lower confidence interval of the beta from the fixed-effects model.</li> <li><em>BETA_UPPER_FIXED</em> - 95% upper confidence interval of the beta from the fixed-effects model.</li> <li><em>BETA_GC</em> - beta after correcting the fixed-effects beta for genomic inflation.</li> <li><em>SE_GC</em> - standard error after correcting the fixed-effects SE for genomic inflation.</li> <li><em>Z_GC</em> - Z-score after correcting the fixed-effects Z-score for genomic inflation.</li> <li><em>P_GC</em> - P-value after correcting the fixed-effects p-value for genomic inflation.</li> <li><em>BETA_RANDOM</em> - beta from the random-effects model.</li> <li><em>SE_RANDOM</em> - standard error from the random-effects model.</li> <li><em>Z_RANDOM</em> - Z-score from the random-effects model.</li> <li><em>P_RANDOM</em> - P-value from the random-effects model.</li> <li><em>BETA_LOWER_RANDOM</em> - 95% lower confidence interval of the beta from the random-effects model.</li> <li><em>BETA_UPPER_RANDOM</em> - 95% upper confidence interval of the beta from the random-effects model.</li> <li><em>COCHRANS_Q</em> - Cochran's Q as a measure of heterogeneity between studies (<a href="https://wiki.joannabriggs.org/pages/viewpage.action?pageId=9273407">see this wiki</a>).</li> <li><em>DF</em> - degrees of freedom, equals the number of studies included for the respective variant (<em>N</em>) minus 1, <em>i.e.</em> <em>DF = N-1</em>.</li> <li><em>P_COCHRANS_Q</em> - P-value of Cochran's heterogeneity test.</li> <li><em>I_SQUARED</em> - <em>I<sup>2</sup></em> as a measure of heterogeneity between studies (<a href="https://wiki.joannabriggs.org/display/MANUAL/3.3.10.2+Quantification+of+the+statistical+heterogeneity%3A+I+squared">see this wiki</a>).</li> <li><em>TAU_SQUARED</em> - <em>Tau<sup>2</sup></em> as a measure of true heterogeneity between studies (<a href="https://wiki.joannabriggs.org/display/MANUAL/3.3.10.3+Tau-squared+for+random+effects+model+meta-analysis">see this wiki</a>).</li> <li><em>DIRECTIONS</em> - the sign of beta in each contributing cohort, annotated as “.” if the variant is missing from a particular cohort.</li> <li><em>GENES_250KB</em> - list of all genes as mapped using GENCODE v19 (GRCh37, hg19, Feb2009) with 250kb.</li> <li><em>NEAREST_GENE</em> - the gene closest to the respective variant.</li> <li><em>NEAREST_GENE_ENSEMBLID</em> - the ENSEMBLID of the nearest gene.</li> <li><em>NEAREST_GENE_STRAND</em> - strand on which the nearest gene is present.</li> <li><em>VARIANT_FUNCTION</em> - variant function as taken from dbSNP v150.</li> <li><em>CAVEAT</em> - potential issue as reported by <a href="https://github.com/swvanderlaan/MetaGWASToolKit">MetaGWASToolKit</a>, <em>e.g.</em> if the variant is an A/T or C/G SNP with allele frequency between 0.35 and 0.65 (indicating strandedness ambiguity).</li> <li><em>QC</em> - utility column, can be used to filter out all the variants with <em>e.g.</em> 'CAF' < 0.001, 'DF' <= 2, 'N_EFF' < 5000 and 'CAVEAT' having an issue depending on the dataset used (discovery, replication, or combined).</li> </ul> <p> </p>
Household survey data linked to Urban Structure Type (UST) for the city of Stuttgart, Germany
<p><span>An overview of the household survey data conducted at Stadtteile scale in the city of Stuttgart and its link with spatial datasets i.e., urban structure types (USTs) are provided in this document. </span></p>
Assessing and mapping the potential development of forest ecosystems, link to research data and scientific software
<p>Research data and scientific software related to: Schröder W. Nickel S, Jenssen M, Riediger J 2015. Methodology to assess and map the potential development of forest ecosystems exposed to climate change and atmospheric nitrogen deposition: a pilot study in Germany. Science of the Total Environment 521-522:108-122</p>
Modelling and mapping heavy metal accumulation in moss and natural surface soil throughout Norway (1990-2010), link to research data and scientific software
<p>Research data and scientific software related to an investigation of statistical relations between the accumulation of heavy metals in moss and natural surface soil and potential influencing factors such as atmospheric deposition. Data were collected in 1995, 2000, 2005 and 2010 throughout Norway. Statistical correlations of a set of potential predictors (elevation, precipitation, density of different land uses, population density, physical properties of soil) with concentrations of cadmium, mercury and lead in moss and natural surface soil were evaluated. Spatio-temporal trends were estimated by use of multivariate regression-kriging and generalized linear models.</p>
Correlating heavy metal deposition and respective concentration in moss and natural surface soil for ecological land classes in Norway (1990-2010), link to research data and scientific software
<p>Research data and scientific software related to a study on statistical correlations between modelled atmospheric heavy metal deposition and respective accumulation in moss and natural surface soil for different natural landscapes in Norway. Data on cadmium, lead, and mercury were collected in 1995, 2000, 2005 and 2010 throughout Norway. The landscape information was derived from the Ecological Land Classification of Europe. Correlations between concentration and respective modelled deposition data were computed for each land class.</p>
Integrative evaluation of biomonitoring data and modelings indicating atmospheric deposition of heavy metals, link to research data and scientific software
<p>Research data and scientific software related to integrative statistical analyses based on deposition data calculated with the model LOTOS-EUROS (LE) and the EMEP/MSC-East model (Germany, Europe) and Biomonitoring data on As, Cd, Cr, Cu, Ni, Pb, Zn concentrations in moss, leaves and needles and soil derived from the European Moss Survey (EMS), the German Environmental Specimen Bank (ESB) and the International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests). The modelled HM deposition and respective concentrations in moss (EMS), leaves and needles (ESB, ICP Forests) and soil (ICP Forests) were investigated for their statistical relationships. Regression kriging was applied to calculate maps of Cd and Pb deposition across Germany.</p>
Random Forest models and maps of heavy metal and nitrogen concentrations in moss in 2010 across Europe, link to research data and scientific software
<p>Research data and scientific software related to a study exploring the statistical relations between the concentration of nine heavy metals (As, Cd, Cr, Cu, Hg, Ni, Pb, V, Zn) and N in moss specimens collected in 2010 throughout Europe and a set potential explanatory variables (such as the atmospheric deposition calculated by use of two chemical transport models, distance from emission sources, density of different land uses, population density, elevation, precipitation, clay content of soils). Statistical analysis and modelling relies on Random Forest (RF). RF-models in conjunction with a Geographical Information System (GIS) were then used for mapping spatial patterns of element concentrations in moss across Europe.</p>
Data set. Exploring the link between cation exchange capacity and magnetic susceptibility
Open the record for dataset details and reuse information.
Modelling spatial patterns of correlations between concentrations of heavy metals in mosses and atmospheric deposition across Europe in 2010, link to research data and scientific software
<p>Research data and scientific software related to a study investigating the correlations between the concentrations of nine heavy metals in moss and atmospheric deposition within ecological land classes covering Europe. Additionally, it is examined to what extent the statistical relations are affected by the land use around the moss sampling sites.</p>
LINKING SEDIMENT THERMAL INERTIA TO DEPOSITIONAL CONTEXT ON EARTH AND MARS: DATA
<p>Thermophysical, grain, and spectroscopic data collected from Mars-analog field sites on Earth.</p>
Raw ILLUMINA NGS data from study on Mouse virulence of European type III and type II x III-recombinant natural clones of Toxoplasma gondii is not always linked to the ROP18 and ROP5 genotype
<ul> <li>Whole genome sequences of naturally recombinant European type III and type II x III clones were analyzed</li> <li>While two of the type II x III recombinants showed an intermediate mouse virulence, a type III clone was highly virulent </li> <li>Of the three highly virulent clones, only two showed a virulent <em>ROP18</em>-<em>ROP5</em> allele combination</li> <li>The mouse virulent type III clone without virulent <em>ROP18</em>-<em>ROP5</em> allele combination showed the highest level of ROP5 mRNA expression</li> <li>Two genetically similar clones showed apparent differences in virulence and corresponding IL-12 mRNA expression in infected macrophages </li> </ul>
raw data and code: Climate deterioration and subsistence economy in prehistoric southern Iberia: an evaluation of potential links based on regional trajectories
<p>Here the raw data and R code for reproducing the study 'Climate deterioration and subsistence economy in prehistoric southern Iberia: an evaluation of potential links based on regional trajectories' of Schirrmacher et al. submitted to PlosOne in July 2023 are archived.</p>
Fig. 3 in An integrated analysis of hyperspectral and morphological data of cicada ovipositors revealed unexplored links to specific oviposition hosts
Fig. 3 Morphological characters of ovipositors used for measurements. a, b First valvulae in lateral view; c base of first valvulae in dorsal view; d apex of first valvulae in dorsal view. Section A: base of ovipositor; Section B: body part of ovipositor; Section C: front claw of ovipositor
Fig. 1 in An integrated analysis of hyperspectral and morphological data of cicada ovipositors revealed unexplored links to specific oviposition hosts
Fig. 1 Oviposition of cicadas Subpsaltria yangi in live twig of Ziziphus jujuba Mill. var. spinosa (a–c) and Karenia caelatata in dead twig of Quercus aliena var. acuteserrata (d–f). a A female of S. yangi; d a female of K. caelatata; b, e egg nests (En) on twigs; c, f sets of eggs. Scale bars: c 1.0 mm; e, f 5.0 mm; a, b, d are not to scale
X-linked H3K27me3 demethylase Utx is required for embryonic development in a sex-specific manner [ChIP-Seq data]
GEO Series GSE39472. Mus musculus. 12 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Couple transcriptome and genomic data obtained from the PDXs to identify pathways linking oncogenic alterations
GEO Series GSE129563. Homo sapiens. 21 samples. Type: Expression profiling by high throughput sequencing.
Data to Support 'Persistent cloud cover over mega-cities linked to surface heat release'
<p>"Persistent cloud cover over mega-cities linked to surface heat release<br> by Theeuwes et al., 2019 NPJ Climate and atmospheric science</p> <p>HRV_london_landuse.txt</p> <ul> <li>HRV processed time series of cloud fractions [-] over each land use type (pixels have to be 100% of one land use class) <ul> <li>"high" - forest/high vegetation </li> <li>"low" - low vegetation</li> <li>"urban" - urban areas </li> <li>"water" - water bodies for London domain.</li> </ul> </li> </ul> <p>HRV_paris_landuse.txt -</p> <ul> <li>HRV processed time series of cloud fractions over each land use type (pixels have to be 100% of one land use class) <ul> <li>"high" - forest/high vegetation,</li> <li>"low" - low vegetation,</li> <li>"urban" - urban areas for Paris domain.</li> </ul> </li> </ul> <p>"london_CBH.csv" -</p> <ul> <li>Cloud base heights ("CBH_L") [m] from CL31 ceilometer at London site (Marylebone road) and logical array whether it is clear or clouds are observed in the 15-min period "clear_L, cloudy_L"</li> </ul> <p>"chilbolton_CBH.csv" -</p> <ul> <li>Cloud base heights ("CBH_C") [m] from CL75K ceilometer at Chilbolton site and logical array whether it is clear or clouds are observed in the 15-min period "clear_C, cloudy_C"</li> </ul> <p>raw data: doi:10.5285/1aa2df5a-798b-46c7-b74a-421f9ca0aa82</p> <p>"london_met.csv" -</p> <ul> <li>Data from meteorological measurements at London (Kings College London site): <ul> <li>"DIP_L" - dew point depression (air temperature - dew point temperature) [K], </li> <li>"RR_L" - precipitation [mm],</li> <li>"T_L" - absolute air temperature [K],</li> <li>"Td_L" - dew point temperature [K].</li> </ul> </li> </ul> <p>"chilbolton_met.csv" -</p> <ul> <li>Data from meteorological measurements at Chilbolton: <ul> <li>"DIP_C" - dew point depression (air temperature - dew point temperature) [K],</li> <li>"T_C" - absolute air temperature [K],</li> <li>"Td_C" - dew point temperature [K].</li> </ul> </li> </ul> <p>"london_fluxes.csv"</p> <ul> <li>- Kinematic sensible ("wth_L" [K m s-1]) and latent heat ("wq_L" [kg kg-1 m s-1]) fluxes at London (Kings College London site).</li> </ul> <p>"chilbolton_fluxes.csv"</p> <ul> <li>- Kinematic sensible ("wth_C" [K m s-1]) and latent heat ("wq_C" [kg kg-1 m s-1]) fluxes at Chilbolton.</li> </ul> <p><br> "2011_chil_lidarwstats.nc"</p> <ul> <li>- Hourly statistics of the LiDAR stare data for Chilbolton site. Vertical velocity variance corrected.</li> </ul> <p>Note: all Chilbolton raw data: http://catalogue.ceda.ac.uk/uuid/7cbc3fc19bfa037a48ba4cba4b93544d</p>
Time series data and codes from: Quantifying links between social media and the duration and escalation of violence during January 6th US Capitol insurrection
Open the record for dataset details and reuse information.
Where are the data linking infant outcomes, breastfeeding and medicine exposure? A systematic scoping review
<p>We conducted a scoping review using systematic searches to map and locate the databases providing quantitative evidence on medicines exposure, breastfeeding and infant outcomes.</p> <p>This work has been undertaken under the auspices of the ConcePTION project. The ConcePTION project has received funding from the <a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.imi.europa.eu%2F&data=05%7C01%7CA.L.Roberts%40Swansea.ac.uk%7C4fb16df80e2240be4d3208db2a0c12aa%7Cbbcab52e9fbe43d6a2f39f66c43df268%7C0%7C0%7C638150003552158701%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=77V2eG01NyKN9s%2BsaetccS5bva0RyrpT73WrXcOaxgA%3D&reserved=0">Innovative Medicines Initiative</a> 2 Joint Undertaking under grant agreement No 821520. This Joint Undertaking receives support from the European Union’s <a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fec.europa.eu%2Fprogrammes%2Fhorizon2020%2F&data=05%7C01%7CA.L.Roberts%40Swansea.ac.uk%7C4fb16df80e2240be4d3208db2a0c12aa%7Cbbcab52e9fbe43d6a2f39f66c43df268%7C0%7C0%7C638150003552158701%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=1%2FsRhMjzsyvtbNgbJxDGfjtx706DbcjGpJv%2F2MS1BIw%3D&reserved=0">Horizon 2020</a> research and innovation programme and <a href="https://eur03.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.efpia.eu%2F&data=05%7C01%7CA.L.Roberts%40Swansea.ac.uk%7C4fb16df80e2240be4d3208db2a0c12aa%7Cbbcab52e9fbe43d6a2f39f66c43df268%7C0%7C0%7C638150003552314962%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=NtPG2ybwZem1u7W2r%2BT1yk5zHD8O0OyaHMlef%2BegBeU%3D&reserved=0">EFPIA</a>. Funding was awarded to Sue Jordan, Sue Lopez. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</p>
Development of molecular markers linked to powdery mildew resistance gene Pm4b by combining SNP discovery from transcriptome sequencing data with bulked segretant analysis (BSR-seq) in wheat
GEO Series GSE108697. Triticum aestivum. 2 samples. Type: Genome variation profiling by high throughput sequencing.
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.