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10.1186/s13073-017-0414-4 http://scihub22266oqcxt.onion/10.1186/s13073-017-0414-4 C5339960!5339960!28270201     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=28270201&cmd=llinks): Failed to open stream: HTTP request failed! 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Exploration of haplotype research consortium imputation for genome-wide association studies in 20,032 Generation Scotland participants |pdf=|usr=}}{{28270201}} gab.com Text Exploration of haplotype research consortium imputation for genome-wide association studies in 20,032 Generation Scotland participants JO: Genome Med http://www.kidney.de/pget.php?&tw=1&pmid=28270201 #FOAvip Background: The Generation Scotland: Scottish Family Health Study (GS:SFHS) is a family-based population cohort with DNA, biological samples, socio-demographic, psychological and clinical data from approximately 24,000 adult volunteers across Scotland. Although data collection was cross-sectional, GS:SFHS became a prospective cohort due to of the ability to link to routine Electronic Health Record (EHR) data. Over 20,000 participants were selected for genotyping using a large genome-wide array. Methods: GS:SFHS was analysed using genome-wide association studies (GWAS) to test the effects of a large spectrum of variants, imputed using the Haplotype Research Consortium (HRC) dataset, on medically relevant traits measured directly or obtained from EHRs. The HRC dataset is the largest available haplotype reference panel for imputation of variants in populations of European ancestry and allows investigation of variants with low minor allele frequencies within the entire GS:SFHS genotyped cohort. Results: Genome-wide associations were run on 20,032 individuals using both genotyped and HRC imputed data. We present results for a range of well-studied quantitative traits obtained from clinic visits and for serum urate measures obtained from data linkage to EHRs collected by the Scottish National Health Service. Results replicated known associations and additionally reveal novel findings, mainly with rare variants, validating the use of the HRC imputation panel. For example, we identified two new associations with fasting glucose at variants near to Y_RNA and WDR4 and four new associations with heart rate at SNPs within CSMD1 and ASPH, upstream of HTR1F and between PROKR2 and GPCPD1. All were driven by rare variants (minor allele frequencies in the range of 0.08?1%). Proof of principle for use of EHRs was verification of the highly significant association of urate levels with the well-established urate transporter SLC2A9. Conclusions: GS:SFHS provides genetic data on over 20,000 participants alongside a range of phenotypes as well as linkage to National Health Service laboratory and clinical records. We have shown that the combination of deeper genotype imputation and extended phenotype availability make GS:SFHS an attractive resource to carry out association studies to gain insight into the genetic architecture of complex traits. Electronic supplementary material: The online version of this article (doi:10.1186/s13073-017-0414-4) contains supplementary material, which is available to authorized users. Twit Text FOAVip Exploration of haplotype research consortium imputation for genome-wide association studies in 20,032 Generation Scotland participants ????Genome Med http://www.kidney.de/pget.php?&tw=1&pmid=28270201 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28270201 #FOAvip English Wikipedia <ref>{{Cite pmid|28270201}}</ref> Exploration of haplotype research consortium imputation for genome-wide association studies in 20,032 Generation Scotland participants #MMPMID28270201 Nagy R; Boutin TS; Marten J; Huffman JE; Kerr SM; Campbell A; Evenden L; Gibson J; Amador C; Howard DM; Navarro P; Morris A; Deary IJ; Hocking LJ; Padmanabhan S; Smith BH; Joshi P; Wilson JF; Hastie ND; Wright AF; McIntosh AM; Porteous DJ; Haley CS; Vitart V; Hayward C Genome Med 2017[]; 9 (ä): ä PMID28270201show ga Background: The Generation Scotland: Scottish Family Health Study (GS:SFHS) is a family-based population cohort with DNA, biological samples, socio-demographic, psychological and clinical data from approximately 24,000 adult volunteers across Scotland. Although data collection was cross-sectional, GS:SFHS became a prospective cohort due to of the ability to link to routine Electronic Health Record (EHR) data. Over 20,000 participants were selected for genotyping using a large genome-wide array. Methods: GS:SFHS was analysed using genome-wide association studies (GWAS) to test the effects of a large spectrum of variants, imputed using the Haplotype Research Consortium (HRC) dataset, on medically relevant traits measured directly or obtained from EHRs. The HRC dataset is the largest available haplotype reference panel for imputation of variants in populations of European ancestry and allows investigation of variants with low minor allele frequencies within the entire GS:SFHS genotyped cohort. Results: Genome-wide associations were run on 20,032 individuals using both genotyped and HRC imputed data. We present results for a range of well-studied quantitative traits obtained from clinic visits and for serum urate measures obtained from data linkage to EHRs collected by the Scottish National Health Service. Results replicated known associations and additionally reveal novel findings, mainly with rare variants, validating the use of the HRC imputation panel. For example, we identified two new associations with fasting glucose at variants near to Y_RNA and WDR4 and four new associations with heart rate at SNPs within CSMD1 and ASPH, upstream of HTR1F and between PROKR2 and GPCPD1. All were driven by rare variants (minor allele frequencies in the range of 0.08?1%). Proof of principle for use of EHRs was verification of the highly significant association of urate levels with the well-established urate transporter SLC2A9. Conclusions: GS:SFHS provides genetic data on over 20,000 participants alongside a range of phenotypes as well as linkage to National Health Service laboratory and clinical records. We have shown that the combination of deeper genotype imputation and extended phenotype availability make GS:SFHS an attractive resource to carry out association studies to gain insight into the genetic architecture of complex traits. Electronic supplementary material: The online version of this article (doi:10.1186/s13073-017-0414-4) contains supplementary material, which is available to authorized users. äExploration of haplotype research consortium imputation for genome-wid(epmc).pdf DeepDyve Pubget Overpricing