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Global coastal transect type classification associated to "Global distribution and dynamics of muddy coasts", Nat. Coms 2023
<p>This dataset is associated with the scientific article "Global distribution and dynamics of muddy coasts" (https://www.nature.com/articles/s41467-023-43819-6)</p> <p>The dataset contains the following items:</p> <ul> <li>VisualizeResults.qgz: QGIS project with the formatted datasets ready for viewing (tested in QGIS v3.28.2.)</li> <li>PredictedClasses_MuddyBeaches.shp (and associated files): Shapefile containing predicted classes of coastal transects differentiating the following types: <ul> <li>0: Sandy coastal transect</li> <li>1: Muddy coastal transect</li> <li>2: Rocky coastal transect</li> <li>3: Vegetated coastal transect</li> <li>4: Other undefined type</li> </ul> </li> <li>MuddyZonesFleming.shp (and associated files): Shapefile containing hand-drawn polygons based on the description of muddy coastline concentrations by (Flemming, B. W. Geographic distribution of muddy coasts, 2002).</li> <li>TransectTrainingDataframe.csv : comma separated value file containing 1867 hand-labelled coastal type transects randomly distributed around the world. Each transect contains the following entries: <ul> <li>transect_id: individual transect ID</li> <li>box_id: tiled ID</li> <li>country_name</li> <li>continent</li> <li>New_Start_lon: longitude transect start</li> <li>New_Start_lat: latitude transect start</li> <li>New_End_lon: longitude transect end</li> <li>New_End_lat: latitude transect end</li> <li>Center_lon</li> <li>Center_lat</li> <li>Length: transect length</li> <li>label: hand-labeled coastal type, Str (Sandy, Muddy, Rocky, Vegetated, Other)</li> <li>abs lat: latitude</li> <li>flag_sandy: bool, classified as a sandy area (Luiijendijk et al, 2018)</li> <li>sand: % of pixels classified as sand from Sentinel 2 Multispectral land-type classification</li> <li>mud: % of pixels classified as muddy from Sentinel 2 Multispectral land-type classification</li> <li>water: % of pixels classified as water from Sentinel 2 Multispectral land-type classification</li> <li>vegetation: % of pixels classified as vegetation from Sentinel 2 Multispectral land-type classification</li> <li>dry: % of pixels classified as dry-vegetation from Sentinel 2 Multispectral land-type classification</li> <li>other: % of pixels classified as other from Sentinel 2 Multispectral land-type classification</li> <li>turbid % of pixels classified as turbid-water from Sentinel 2 Multispectral land-type classification</li> <li>height max: max height in transect (MERIT-DEM)</li> <li>height var: variance height in transect (MERIT-DEM)</li> <li>mangrove: bool, mangrove presence (Global Mangrove Forest Distributions)</li> <li>intertidal: intertidal range Murray et al 2019.</li> <li>gsw: Global Surface Water dataset, Pekel et al 2016</li> <li>maxtemp: max temperature WorldClim V1 Bioclim dataset</li> <li>mintemp: min temperature WorldClim V1 Bioclim dataset</li> <li>mhhw: Tide MHHW Deltares GTSM model</li> <li>mllw: Tide MLLW Deltares GTSM model</li> <li>tidal range: Tidal range Deltares GTSM model</li> </ul> </li> <li>PixelTrainingDataframe.csv : comma separated value file containing 3240 hand-labelled land-type pixel randomly distributed around the world. These are derived from a Sentinel 2 TOA images as a 2020 composite. Bands (BX) refer to the Sentinel-2 MSI Multispectral Instrument, level-2A spectral bands names. Each entry contains: <ul> <li>Aerosols: B1</li> <li>Blue: B2</li> <li>Green: B3</li> <li>Red: B4</li> <li>Red Edge 1: B5</li> <li>Red Edge 2: B6</li> <li>Red Edge 3: B7</li> <li>NIR: B8</li> <li>Red Edge 4: B8A</li> <li>SWIR 1: B11</li> <li>SWIR 2: B12</li> <li>NDWI: Normalized Differential Water Index ((B3-B8)/(B3+B8)</li> <li>NDVI ((B8-B4)/(B8+B4)</li> <li>num: hand-label type differentiating the following types (1) sandy beaches, (2) mudflats, (3) clear water, (4) 111 turbid (brown) water, (5) green vegetation, (6) dry vegetation, and (7) other (containing clouds, snow, buildings, and all other indefinable points)</li> </ul> </li> </ul>
Dataset incr1 - NGS-based S. aureus typing and outbreak analysis in clinical microbiology laboratories: lessons learned from a Swiss-wide proficiency test
<p>Supplemental material of article "NGS-based S. aureus typing and outbreak analysis in clinical microbiology laboratories: lessons learned from a Swiss-wide proficiency test" by D. Dylus et al. Please refer to Methods therein.</p> <p>FASTQ datasets for increment 1. </p>
Data for "Brain cell-type shifts in Alzheimer's disease, autism and schizophrenia interrogated using methylomics and genetics"
<p>Data for "Genetic and methylomic interrogation of brain cell-type shifts in autism, schizophrenia, and Alzheimer’s disease" (Yap et al. 2023).</p> <p>Source data from ROSMAP, LIBD and UCLA_ASD post-mortem brain datasets.</p> <p>This data repository contains 3 files:</p> <p><strong>220819_Supplementary_Tables.xlsx</strong></p> <p>Supplementary Tables for the manuscript:</p> <ol> <li>Supplementary Table 1: Comparison of CTP deconvolution methods in the ROSMAP dataset. mcc* denotes methylCC deconvolution; sSV* denotes smartSVA; h* indicates Houseman using array reference data; hseq* indicates Houseman with sequencing reference data; celfie* indicates CelFIE (and includes an output titled "unknown1"); VAEe* indicates variational autoencoder embeddings.</li> <li>Supplementary Table 2: Comparison of CTP deconvolution methods in the LIBD dataset. mcc* denotes methylCC deconvolution; sSV* denotes smartSVA; h* indicates Houseman using array reference data; hseq* indicates Houseman with sequencing reference data; celfie* indicates CelFIE (and includes an output titled "unknown1"); VAEe* indicates variational autoencoder embeddings.</li> <li>Supplementary Table 3: Comparison of CTP deconvolution methods in the UCLA_ASD dataset. mcc* denotes methylCC deconvolution; sSV* denotes smartSVA; h* indicates Houseman using array reference data; hseq* indicates Houseman with sequencing reference data; celfie* indicates CelFIE (and includes an output titled "unknown1"); VAEe* indicates variational autoencoder embeddings.</li> <li>Supplementary Table 4: Deconvolved brain CTPs (raw), with covariates.</li> <li>Supplementary Table 5: Deconvolved brain CTPs (clr-transform, offset 1e-3), with covariates and raw PGS for all ancestries. Comp* indicates compositionally-aware principal components of the CTP data; *pgs_raw indicates PGS calculated for using genotyping across all ancestries. This table has a total of n=1,098 across all ancestries, including n=885 EUR. After applying a rel<0.05 threshold on the n=885 EUR, there were n=878 EUR which were used in the PGS analysis so that population stratification PCs did not simply capture family structure.</li> <li>Supplementary Table 6: Deconvolved brain CTPs (clr-transform, offset 1e-3), with covariates and standardised PGS for n=878 Europeans. *pgs_raw indicates unstandardised PGS, PC* indicates genotyping PCs within the European dataset, *_PGS indicates standardised PGS within the European subset.</li> <li>Supplementary Table 7: Deconvolved brain CTPs (clr-transform, offset 1e-3), adjusted for oligodendrocyte proportions, with covariates.</li> <li>Supplementary Table 8: Deconvolved brain CTPs (raw), adjusted for oligodendrocyte proportions, with covariates.</li> </ol> <p><strong>20220108_maf05_gwas_ctp.tar.gz</strong></p> <p>GWAS summary statistics for the 7 brainCTPs (clr-transformed): Exc, Inh, Astro, Endo, Micro, Oligo, OPC</p> <p>METAL output format:<br> MarkerName: SNP<br> Allele1<br> Allele2<br> Freq1: Allele1 frequency<br> FreqSE: frequency standard error<br> MinFreq: minimum Allele1 frequency in meta-analysis<br> MaxFreq: maximum Allele1 frequency in meta-analysis<br> Effect: effect size<br> StdErr: standard error of effect size<br> P-value: calculated in inverse variance weighted meta-analysis<br> Direction: directions of effects across the 3 datasets<br> HetISq: heterozygosity I-squared<br> HetChiSq: heterozygosity chi-squared<br> HetDf: heterozygosity degress of freedom<br> HetPVal: heterozygosity test p-value</p> <p><strong>20220108_maf05_gwas_ctp_pc.tar.gz</strong></p> <p>GWAS summary statistics for the 5 CTP_PCs</p> <p>METAL output format (see above)</p> <p> </p> <p><strong>Source data</strong>:</p> <p>ROSMAP: Raw methylation .idat files were obtained from Synapse accession syn7357283. Whole genome sequencing .vcf files (variants jointly called with MSBB and Mayo studies) were obtained from Synapse accession syn11707420.</p> <p>LIBD: Raw methylation .idat files were obtained from GEO accession GSE74193. SNP genotypes were downloaded from dbGaP accession phs000417.v2.p1.</p> <p>UCLA-ASD: The processed methylation beta matrix was downloaded from Synapse accession syn8263588. SNP genotypes were downloaded from Synapse accession syn10537134.</p> <p>GWAS summary statistics are available at: 10.5281/zenodo.7604231</p> <p>Code is available on GitHub: gandallab/brain_CTP_deconv</p>
Fig. 32 in Catalogue of type specimens of braconid wasps (Hymenoptera: Braconidae) deposited in the National Museum, Prague, Czech Republic
Fig. 32. Paratypus of Orgilus tobiasi Taeger, 1989 (male) (scale bar = 2.5 mm).
Fig. 27 in Catalogue of type specimens of braconid wasps (Hymenoptera: Braconidae) deposited in the National Museum, Prague, Czech Republic
Fig. 27. Holotype of Opius pulchriventris Fischer, 1958 with its labels (scale bar = 2.5 mm).
Fig. 24 in Catalogue of type specimens of braconid wasps (Hymenoptera: Braconidae) deposited in the National Museum, Prague, Czech Republic
Fig. 24. Holotype of Opius moravicus Fischer, 1960 with its labels (scale bar = 2.5 mm).
Fig. 29 in Catalogue of type specimens of braconid wasps (Hymenoptera: Braconidae) deposited in the National Museum, Prague, Czech Republic
Fig. 29. Paratypus of Orgilus achterbergi Taeger, 1989 (scale bar = 2.5 mm).
Fig. 23 in Catalogue of type specimens of braconid wasps (Hymenoptera: Braconidae) deposited in the National Museum, Prague, Czech Republic
Fig. 23. Hootype of Opius minor Fischer, 1957 with its labels (scale bar = 2.5 mm).
Fig. 20 in Catalogue of type specimens of braconid wasps (Hymenoptera: Braconidae) deposited in the National Museum, Prague, Czech Republic
Fig. 20. Holotype of Opius latipes Fischer, 1958 with its labels (scale bar = 2.5 mm).
Fig. 18 in Catalogue of type specimens of braconid wasps (Hymenoptera: Braconidae) deposited in the National Museum, Prague, Czech Republic
Fig. 18. Holotype of Opius curtipectus Fischer, 1958 with its labels (scale bar = 2.5 mm).
Fig. 35 in Catalogue of type specimens of braconid wasps (Hymenoptera: Braconidae) deposited in the National Museum, Prague, Czech Republic
Fig. 35. Different type labels used by Maximilian Fischer for material stored in NMPC.
Fig. 15 in Catalogue of type specimens of braconid wasps (Hymenoptera: Braconidae) deposited in the National Museum, Prague, Czech Republic
Fig. 15. Holotype of Opius capeki Fischer, 1963 with its labels (scale bar = 2.5 mm).
Fig. 17 in Catalogue of type specimens of braconid wasps (Hymenoptera: Braconidae) deposited in the National Museum, Prague, Czech Republic
Fig. 17. Holotype of Opius caudifer Fischer, 1958 with its labels (scale bar = 2.5 mm).
Fig. 19 in Catalogue of type specimens of braconid wasps (Hymenoptera: Braconidae) deposited in the National Museum, Prague, Czech Republic
Fig. 19. Holotype of Opius laetatorius Fischer, 1958 with its labels (scale bar = 2.5 mm).
Fig. 12 in Catalogue of type specimens of braconid wasps (Hymenoptera: Braconidae) deposited in the National Museum, Prague, Czech Republic
Fig. 12. Holotype of Apanteles dion Nixon, 1965 with its labels (scale bar = 2.5 mm).
Fig. 7 in Catalogue of type specimens of braconid wasps (Hymenoptera: Braconidae) deposited in the National Museum, Prague, Czech Republic
Fig. 7. Allotype of Cosmophorus roubali Čapek, 1958 with its labels (scale bar = 2.5 mm).
Fig. 14 in Catalogue of type specimens of braconid wasps (Hymenoptera: Braconidae) deposited in the National Museum, Prague, Czech Republic
Fig. 14. Paratype of Opius boučeki (Fischer, 1958) with its labels (scale bar = 2.5 mm).
Fig. 6 in Catalogue of type specimens of braconid wasps (Hymenoptera: Braconidae) deposited in the National Museum, Prague, Czech Republic
Fig. 6. Holotype of Cosmophorus roubali Čapek, 1958 with its labels (scale bar = 2.5 mm).
Fig. 5 in Catalogue of type specimens of braconid wasps (Hymenoptera: Braconidae) deposited in the National Museum, Prague, Czech Republic
Fig. 5. Allotype of Dendrosotinus similis Bouček, 1955 with its labels (scale bar = 2.5 mm).
Fig. 10 in Catalogue of type specimens of braconid wasps (Hymenoptera: Braconidae) deposited in the National Museum, Prague, Czech Republic
Fig. 10. Holotype of Rogadiaspis tritoma Bouček, 1956 with its labels (scale bar = 2.5 mm).
ScienceDex guides
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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.