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2,880 results for “variant”
Coordinates of genetic variants used for QTL mapping
<p>Column names</p> <ol> <li>chr - chromosome name</li> <li>pos - position</li> <li>snp_id - variant id</li> <li>ref - reference allele</li> <li>alt - alternate allele</li> <li>type - variant type (SNP or INDEL)</li> <li>AC - alternate allele count</li> <li>AN - total allele count</li> </ol>
Human genetic variants and age are the strongest predictors of humoral immune responses to common pathogens and vaccines
<p>Online Supplementary Dataset of the manuscript "Human genetic variants and age are the strongest predictors of humoral immune responses to common pathogens and vaccines"</p>
Human variant calling data
<p>Short read data from the exome of chromosome 22 of a single human individual. There are one million 76bp reads in the dataset, produced on an Illumina GAIIx from exome-enriched DNA. This data was generated as part of the 1000 Genomes project.</p>
Bridging the Chromosome-Centric and Biology and Disease Human Proteome Projects: Accessible and automated tools for interpreting biological and pathological impact of protein sequence variants detected via proteogenomics
<p>Bridging the Chromosome-Centric and Biology and Disease Human Proteome Projects: Accessible and automated tools for interpreting biological and pathological impact of protein sequence variants detected via proteogenomics</p>
Mapping cis-regulatory chromatin contacts in neural cells links neuropsychiatric disorder risk variants to target genes
<p>ATAC-seq peaks are in narrowPeak format. RNA-seq results are organized according to cell type. The normalized RPKM is reported for each gene in GENCODE 19. All data was mapped to hg19.</p>
Leaf responses to mild drought stress in natural variants of Arabidopsis.
<p>Plant growth and crop yield are negatively affected by a reduction in water availability. However, a clear understanding of how growth is regulated under non-lethal drought conditions is lacking. Recent advances in genomics, phenomics and transcriptomics allow in-depth analysis of natural variation. In this study, we conducted a detailed screening of leaf growth responses to mild drought in six <em>Arabidopsis thaliana</em> accessions. </p> <p>The raw phenotyping can be found in:<br> - cellularData.txt -> mature (22 days after stratification; DAS) leaf epidermis (third leaf) analysed for cell area, cell number, pavement cell area, pavement cell number, stomatal index and leaf area of the analysed leaf.</p> <p>- leaf3_maturity.txt -> area of the third leaf at maturity (22DAs) in mm<sup>2.</sup></p> <p>- leaf3_transition.txt -> area of the third leaf at transition (last day of cell proliferation; 11 DAS) in mm<sup>2</sup>.</p> <p>- rosetteArea.txt -> projected rosette area (mm<sup>2</sup>) over time (from 9-21DAS).</p> <p>The phenotyping results have been normalised for batch effects ('experiment' in raw data) and are found in cellularData_normalised.txt, leaf3_normalised.txt and rosetteArea_normalised.txt.</p> <p>Conversion from accession names (indiated as genotype in the data files) to the ID number used in the 1001genomes project (www.1001genomes.org) can be found in accessionIDs.txt.</p> <p>In each file 'C' indicates well-watered plants, while 'S' stand for mild-drought treatment.</p> <p>These results and methodological results are described in Clauw et al. (2015, Plant Physiology).</p> <p> </p> <p> </p>
GCTB SBayesR shrunk sparse linkage disequilibrium matrices for HM3 variants, summary statistics and predictors generated from "Improved polygenic prediction by Bayesian multiple regression on summary statistics" by Lloyd-Jones, Zeng et al. 2019.
<p>GCTB LD matrices and results for HapMap 3 variants and 2.8M variants, which were used for</p> <p>simulation, cross-validation and across biobank analyses in the manuscript "Improved polygenic</p> <p>prediction by Bayesian multiple regression on summary statistics" by Lloyd-Jones, Zeng et al.</p> <p>2019.</p> <p>Unzip and see README for further details.</p>
GCTB sparse shrunk LD matrices from 2.8M common variants from the UK Biobank - Part AA - START HERE
<p>GCTB sparse shrunk LD matrices from 2.8M common variants from the UK Biobank.</p> <p>Part <strong>AA </strong>of AA, AB, AC, AD and AE.</p> <p><strong>TO JOIN AND UNZIP THESE MATRICES</strong></p> <p><strong>Download all parts to one folder from:</strong></p> <p> PartAA - 10.5281/zenodo.3375373</p> <p> PartAB - 10.5281/zenodo.3376357</p> <p> Part AC - 10.5281/zenodo.3376456</p> <p> Parts AD and AE - 10.5281/zenodo.3376628</p> <p><strong>Use cat to join </strong></p> <p>cat <a href="https://zenodo.org/api/files/8ffd1abc-07ef-4b8a-a6cf-779a73ee03c2/ukb_50k_bigset_2.8M.zip.partaa?versionId=102ded84-352a-494d-8da3-cebb63a20aee">ukb_50k_bigset_2.8M.zip.part* > ukb_50k_bigset_2.8M.zip </a></p> <p>Then unzip. See README for further details.</p> <p>unzip <a href="https://zenodo.org/api/files/8ffd1abc-07ef-4b8a-a6cf-779a73ee03c2/ukb_50k_bigset_2.8M.zip.partaa?versionId=102ded84-352a-494d-8da3-cebb63a20aee">ukb_50k_bigset_2.8M.zip </a></p>
NGSAP-VC : Genomic Variant Calling as an Installable GALAXY Workflow Using NGS data.
<p>Implementation of genomic variants calling as an installable GALAXY workflows using NGS data. Repository contains two separate sets of simulated ebola test data. One for SNPs and INDELs calling and another for Structural Variants calling.</p>
VCF file of an individual with a variant in the RLIM gene
<p>The VCF file was obtained from whole-exome sequencing data of a DNA sample from an individual with a likely pathogenic variant in the RLIM gene (MIM 300379), which causes Tønne-Kalscheuer syndrome (MIM 300978).</p> <ul> <li>proband.vcf is a file of an affected individual (proband) with a variant in the RLIM gene.</li> </ul>
MIGNEX Survey metadata (restricted-access variant)
<p>This is a metadata record representing the restricted-access variant of the MIGNEX survey dataset. The data file is stored on the project's internal file hosting service, as "...\\MIGNEX-data\WP03-data\MIGNEX-Survey-dataset\mxs-restricted-v1.dta". It cannot be uploaded to Zenodo because it contains potentially identifying information.</p>
Datasets belonging to the publication "Allelic variants confer Arabidopsis adaptation to small regional environmental differences".
<p>Datasets belonging to the publication "Allelic variants confer Arabidopsis adaptation to small regional environmental differences".</p> <p>A short description of each file is found below. Samples in the Variant Call Format (VCF) files are named according to how they are stored in the National Center for Biotechnology Information (NCBI) BioSample database. Detailed descriptions of how each file was generated are found in the manuscript.</p> <p><strong>Dartmap_Dutch_1001G_nuclear.vcf.gz</strong></p> <p>2,712,612 bi-allelic SNPs and 353,974 bi-allelic small indels called in the DartMap panel and the Dutch 1001G accessions (collectively referred to as DartMap + 1001G panel for brevity) relative to the <em>Arabidopsis thaliana</em> Col-0 nuclear genome reference sequence.</p> <p><strong>Dartmap_Dutch_1001G_mitochondrial.vcf.gz</strong></p> <p>231 bi-allelic SNPs and 23 bi-allelic small indels called in the DartMap panel and the Dutch 1001G accessions (collectively referred to as DartMap + 1001G panel for brevity) relative to the <em>A. thaliana</em> Col-0 mitochondrial genome reference sequence.</p> <p><strong>Dartmap_Dutch_1001G_chloroplast.vcf.gz</strong></p> <p>400 bi-allelic SNPs and 79 bi-allelic small indels called in the DartMap panel and the Dutch 1001G accessions (collectively referred to as DartMap + 1001G panel for brevity) relative to the <em>A. thaliana</em> Col-0 chloroplast genome reference sequence.</p> <p><strong>Dartmap_CNVs.vcf.gz</strong></p> <p>29,155 copy number variants (CNVs) called in the DartMap panel relative to the <em>A. thaliana</em> Col-0 reference genome.</p> <p><strong>Dartmap_Dutch_1001G_neighbouring_countries_nuclear.vcf.gz</strong></p> <p>Filtered VCF file containing variants of the DartMap + 1001G panel and that of neighbouring countries relative to the <em>A. thaliana</em> Col-0 nuclear genome reference sequence. Used for population structure analysis in the manuscript.</p> <p><strong>Dartmap_Dutch_1001G_neighbouring_countries_mitochondrial.vcf.gz</strong></p> <p>Filtered VCF file containing variants of the DartMap + 1001G panel and that of neighbouring countries relative to the <em>A. thaliana</em> Col-0 mitochondrial genome reference sequence. Used for population structure analysis in the manuscript.</p> <p><strong>Dartmap_Dutch_1001G_neighbouring_countries_chloroplast.vcf.gz</strong></p> <p>Filtered VCF file containing variants of the DartMap + 1001G panel and that of neighbouring countries relative to the <em>A. thaliana</em> Col-0 chloroplast genome reference sequence. Used for population structure analysis in the manuscript.</p> <p><strong>Dartmap_GWAS_GEA.vcf.gz</strong></p> <p>Filtered VCF file containing all variants of the DartMap panel that were used for all genome-wide association (GWA) and genome-environment association (GEA) analyses.</p> <p><strong>DartMap_phenotypical_data.xlsx</strong></p> <p>All relevant phenotypical data of the DartMap panel. </p> <p><strong>Dartmap_sample_ids_NCBI_sample_names.csv</strong></p> <p>Table showing which numerical ID of each DartMap sample corresponds to which NCBI BioSample ID. </p>
Cancer related variants list
<p>We created a set of 71021 protein altering variants related to cancer.<br>The list can be used to annotate or prioritize any mutation lists from Human sequencing experiment.</p> <p>Methods:</p> <p>We selected variants from COSMICv94 (GRCh38) where CNT > 2 excluding those flagged as SNP.<br>The resulting dataset was further annotated using SNPEff (v5.1d) and Clinvar (20240325) using SnpSift (v5.1d).<br>We filtered out all the 'Benign' and 'Likely_benign' as well as all the 'synomnimous_variants'.</p> <p>FOR RESEARCH USE ONLY</p> <p>COSMIC and Clinvar have usage policy restrictions.</p> <p>https://cancer.sanger.ac.uk/cosmic/license<br>https://www.ncbi.nlm.nih.gov/clinvar/docs/maintenance_use/ </p>
Canadian Arctic narwhal and bowhead whale genomic variants
<p>This dataset contains resequencing data used in our Arctic whale genomics research exaiming population structure and demographic history in bowhead whales and narwhal, including unfiltered genomic variants and filtered SNPs. Source code for genomic analyses is available at <a href="http://github.com/edegreef/NBW-resequencing">github.com/edegreef/arctic-whales-resequencing</a>. Data uploaded here contain:</p> <ul> <li><strong>bowhead_sample_info.csv</strong> - metadata for bowhead whale samples</li> <li><strong>bowhead_RWmap_allvariants.vcf.gz</strong> - all variant calls in bowhead whales, including indels and SNPs (n = 21)</li> <li><strong>bowhead_RWmap_snps.filtered.autosomes.vcf.gz </strong>- bowhead whale SNPs filtered for quality, bi-allelic sites, and autosomes (n = 21)</li> <li><strong>bowhead_RWmap_snps.filtered.autosomes.hwe_maf_LDprunedr08_n20.vcf.gz</strong> - bowhead whale SNPs filtered for quality, bi-allelic sites, out of HWE, MAF > 0.05, LD-pruned, removal of close kin (n = 20).<br><br></li> <li><strong>narwhal_sample_info.csv</strong> - metadata for narwhal samples</li> <li><strong>narwhal_allvariants.vcf.gz</strong> - all variant calls in narwhals, including indels and SNPs for bowhead whales (n = 62*)</li> <li><strong>narwhal_snps.filtered.autosomes.vcf.gz </strong>- narwhal SNPs filtered for quality, bi-allelic sites, and autosomes (n = 62*)</li> <li><strong>narwhal_snps.filtered.autosomes.hwe_maf_LDprunedr08_n57.vcf.gz</strong> - narwhal SNPs filtered for quality, bi-allelic sites, out of HWE, MAF > 0.05, LD-pruned, removal of duplicates, close kin, and samples with high missingness (n = 57)</li> </ul> <p>The asterisk* is to note this includes 2 duplicate samples that were removed from the analyses and respective manuscript.</p>
The result of variants calling with the Japonica reference
<p>We used two major varities of the rice genome, Indica and Japonica, to build different variant calling models that differ in the composition of samples from the two varities. </p>
The result of variants calling with the Indica reference
<p>We used two major varities of the rice genome, Indica and Japonica, to build different variant calling models that differ in the composition of samples from the two varities.</p>
TECdisplay data for Clostridium beijerinckii pfl ZTP riboswitch variant libraries
<p>Transcription termination/antitermination efficiency data for the <em>Clostridium beijerinckii</em> <em>pfl</em> ZTP riboswitch variant libraries. Data were generated using the Transcription Elongation Complex Display (TECdisplay) procedure.</p>
Genome-wide comparison reveals large structural variants in the cassava landraces Authors
<p><span>Structural variants (SVs) are critical for plant genomic diversity and phenotypic variation. This study investigates a large, 9.7 Mbp highly repetitive segment on chromosome 12 of <em><span>TMEB117</span></em>, a region not previously characterized in cassava. We aim to explore its presence and variability across multiple cassava landraces, providing insights into its genomic significance and potential implications.</span></p>
POLQ mediates replication-stress induced structural variant formation throughout common fragile sites during mitosis
<p>Larger processed svCapture data files related to the linked publication. Two types of files are provided:</p> <p>1) Data packages, ending in .mdi.package.zip = processed data files that can be loaded by the svCapture Shiny app, or otherwise extracted to explore the contents.</p> <p>2) App bookmarks, ending in .mdi = saved state of the app with stored configurations from which figures were plotted.</p>
Mode-of-inheritance predictions for all possible missense variants in the human genome (hg38)
<p><span>Ensemble and consensus approaches to prediction of recessive inheritance for missense variants in human disease.</span></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.