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Dataset results
376 results for “Causality”
A systems genetics approach implicates USF1, FADS3 and other causal candidate genes for familial combined hyperlipidemia
GEO Series GSE17170. Homo sapiens. 70 samples. Type: Expression profiling by array.
Dissecting Non-Coding GWAS Loci with High-Resolution 3D Chromatin Interactions Reveals Causal Genes with Relevance to Heart Failure [Hi-C]
GEO Series GSE281463. Homo sapiens. 4 samples. Type: Other.
Coupled single-cell CRISPR screening and epigenomic profiling reveals causal gene regulatory networks
GEO Series GSE116297. Homo sapiens. 8711 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Other.
A biallelic multiple nucleotide length polymorphism explains functional causality at the 5p15.33 prostate cancer risk locus [ATAC-Seq]
GEO Series GSE231750. Homo sapiens. 3 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Gene expression during early infection of the resistant spring wheat cultivar Wuhan1 with Fusarium graminearum, the major causal agent of fusarium head blight in wheat
GEO Series GSE54553. Triticum aestivum. 10 samples. Type: Expression profiling by array.
Variant-to-function analysis of the childhood obesity chr12q13 locus implicates rs7132908 as a causal variant within the 3’ UTR of FAIM2
GEO Series GSE241691. Homo sapiens. 59 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing; Other.
Genome-wide enhancer-gene regulatory maps link causal variants to target genes underlying human colorectal cancer risk [ATAC-seq]
GEO Series GSE222766. Homo sapiens. 10 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Identification of causal genes about osteoporosis associated with risk loci using DLO Hi-C [Hi-C]
GEO Series GSE160394. Homo sapiens. 3 samples. Type: Other.
Identification of causal genes about osteoporosis associated with risk loci using DLO Hi-C
GEO Series GSE160396. Homo sapiens. 15 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing; Other.
Infection exposure is a causal factor in B-precursor acute lymphoblastic leukemia as a result of Pax5 inherited susceptibility
GEO Series GSE62529. Mus musculus. 17 samples. Type: Expression profiling by array.
Causal network inference from gene transcriptional time-series response to glucocorticoids
GEO Series GSE144663. Homo sapiens. 199 samples. Type: Expression profiling by high throughput sequencing.
Systems-based analyses of brain regions functionally impacted in Parkinson's disease reveals underlying causal mechanisms
GEO Series GSE54282. Homo sapiens. 33 samples. Type: Expression profiling by array.
Integrating Molecular and Organismal Analyses of Rai1, The Causal Gene for Smith-Magenis Syndrome
GEO Series GSE81207. Mus musculus. 20 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing.
Identification of causal genes about osteoporosis associated with risk loci using DLO Hi-C [RNA-Seq]
GEO Series GSE160389. Homo sapiens. 9 samples. Type: Expression profiling by high throughput sequencing.
Dissecting Non-Coding GWAS Loci with High-Resolution 3D Chromatin Interactions Reveals Causal Genes with Relevance to Heart Failure [Perturb-seq]
GEO Series GSE281464. Homo sapiens. 7 samples. Type: Other.
Comparison between saprotrophic and biotrophic-like mycelia of cacao WBD causal agent Moniliophthora perniciosa
GEO Series GSE9701. Moniliophthora perniciosa. 16 samples. Type: Expression profiling by array.
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>
Automated causal inference in application to randomized controlled clinical trials
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Literal interviews (The Mutual Influence between Entrepreneurial Marketing and Causal and Effectual Entrepreneurship: An Empirical Study in an Emerging and Developing Economy)
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Fig. 3 in Argyrotoxins A-C, a trisubstituted dihydroisobenzofuranone, a tetrasubstituted 2-hydroxyethylbenzamide and a tetrasubstitutedphenyl trisubstitutedbutyl ether produced by Alternaria argyroxiphii, the causal agent of leaf spot on African mahogany trees (Khaya senegalensis)
Fig. 3. Mnemonic scheme relating the absolute configuration and the sign of the A band in the ECD spectrum of biphenylamides. L = largest group, M = medium size group, S = smallest group.
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.