1,721,035 research outputs found
SUPERSEDED - Generation Scotland SFHS Data Dictionary
No full text## This item has been replaced by the one which can be found at https://doi.org/10.7488/ds/2277 . ## The GS:SFHS Data Dictionary is a set of information describing the contents, format, and structure of the phenotype data collected during recruitment (2006-2011) to the Generation Scotland Scottish Family Health Study (GS:SFHS), or derived subsequently from study data collected during recruitment
Generation Scotland SFHS Data Dictionary
Full text linkThe GS:SFHS Data Dictionary is a set of information describing the contents, format, and structure of the phenotype data collected during recruitment (2006-2011) to the Generation Scotland Scottish Family Health Study (GS:SFHS), or derived subsequently from study data collected during recruitment. This dataset replaces the one at https://datashare.is.ed.ac.uk/handle/10283/272
Human genetic variation and disease
No full textThe data forms part of the Resource pack Human genetic variation and disease, which is a real data resource to allow students to explore genetic and phenotypic data as part of their Scottish Qualifications Authority Nat5 or Higher Biology Assignment, http://www.ed.ac.uk/mrc-human-genetics-unit/public-events-resources/inspiring-the-next-generation-of-researchers/school-data-resources
Staff from the MRC Human Genetics Unit worked with the lead biology teachers for Edinburgh and their colleagues to create the resource. The dataset consists of individual level genotype and phenotype of participants in Generation Scotland (Scottish Family Health Study, GS:SFHS), www.generationscotland.org .
This dataset is part of the QTL Collection https://datashare.ed.ac.uk/handle/10283/70
Generation Scotland: Donor DNA Databank
Full text linkThe Generation Scotland Donor DNA Databank (GS:3D) phenotype was collected from consented blood donors by questionnaire and relates to 4,998 healthy control DNA samples and plasma.Dataset pertaining to the publication “Generation Scotland: Donor DNA Databank; A control DNA resource”. BMC Med Genet 2010 Nov 23;11:166. doi: 10.1186/1471-2350-11-166.
URL: http://www.biomedcentral.com/1471-2350/11/166
The data is phenotype information collected from consented donors by questionnaire as described in the research paper and is in an MS Excel table, GS3D phenotype.xls.
If you use this dataset, please cite the manuscript in order to acknowledge the contribution of the Generation Scotland: Donor DNA Databank (GS:3D) resource.
For information about using GS:3D DNA or plasma samples, or genetic data, please visit http://www.generationscotland.org/ or contact [email protected]. All applications to use Generation Scotland resources will be reviewed by the Generation Scotland Access Committee.
GS:3D is an NHS Lothian NRS BioResource, governed as a Research Tissue Bank by the GS Access Committee, and has supported over 20 research projects to date.
GS:3D was funded by a project grant from the Scottish Executive Health Department, Chief Scientist Office, grant number CZB/4/285.
Shona Kerr, on behalf of all co-authors in the corresponding manuscript
Generation Scotland Scottish Family Health Study (SFHS) Data Dictionary
No full textThe GS:SFHS Data Dictionary is a set of information describing the contents, format, and structure of the phenotype data collected during recruitment (2006-2011) to the Generation Scotland Scottish Family Health Study (GS:SFHS), or derived subsequently from study data collected during recruitment.Campbell, Archie; Kerr, Shona; Porteous, David. (2018). Generation Scotland SFHS Data Dictionary, 2006-2011 [dataset]. University of Edinburgh. School of Molecular, Genetic and Population Health Sciences. Institute of Genetics and Molecular Medicine. http://dx.doi.org/10.7488/ds/2277
Viking II Data Dictionary
No full textVIKING II was made possible thanks to Medical Research Council (MRC) funding. We aim to better understand what might cause diseases such as heart disease, eye disease, stroke, diabetes and others by inviting 4,000 people with 2 or more grandparents from Orkney and Shetland to complete a questionnaire and provide a saliva sample. This data dictionary outlines what volunteers were asked and indicates the data you can access. To access the data, please e-mail [email protected], Jim Flett; Buchanan, David; Kerr, Shona M; Edwards, Rachel. (2021). Viking II Data Dictionary, [dataset]. University of Edinburgh. Institute of Genetics and Cancer. MRC Human Genetics Unit. https://doi.org/10.7488/ds/3145
Genome-wide p-values of nine multivariate IgG glycan GWAS
No full textWhole-genome multivariate association results for nine groups of IgG N-glycosylation phenotypes. For the detailed definition of the glycan groups, please refer to Shen et al. (2017) Nature Communications: "Multivariate discovery and replication of five novel loci associated with Immunoglobulin G N-glycosylation". If you use this dataset, please cite the paper in order to fairly acknowledge the contribution of all participating studies and their sponsors. GWAS: Genome-wide association study. SNP: Single nucleotide polymorphism.
The text files are tab-delimited and contain genome-wide SNP names and MANOVA test p-values for the discovery cohort
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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