Bringing genome-wide association findings into clinical use.Eichler, E. E. et al. Whole genome SNP arrays as a potential diagnostic tool for the detection of characteristic chromosomal aberrations in renal epithelial tumors.Deng, W. Q. & Ritchie, M. E. KRLMM: an adaptive genotype calling method for common and low frequency variants.Winchester, L., Yau, C. & Ragoussis, J. & Meyre, D. Challenges in reproducibility of genetic association studies: lessons learned from the obesity field.Bhattacharjee, S. et al. Genetic variation in IL28B predicts hepatitis C treatment-induced viral clearance.Suppiah, V. et al.

Genome-wide association studies of drug response and toxicity: an opportunity for genome medicine.Ge, D. et al. Polygenic contribution in individuals with early-onset coronary artery disease.Natarajan, P. et al. The new NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog).Hirschhorn, J. N. Genomewide association studies — illuminating biologic pathways.Klein, R. J., Xu, X., Mukherjee, S., Willis, J. Descriptions for cell and tissue types, related groups, and marks at the Roadmap Epigenomics Project website (http://www.roadmapepigenomics.org).Top 30 significantly enriched pathways and gene sets in the cross-ethnic meta-analysis (XLSX 10 kb).NGENES denotes the number of genes in pathway (number of genes successfully mapped by MAGMA).Get the most important science stories of the day, free in your inbox.Supplementary Figure 1 PCA of the Chinese GWAS sample with the HapMap3 sample.Supplementary Figure 2 Quantile–quantile (Q–Q) plot of the GWAS analysis of Chinese individuals.Supplementary Figure 3 Manhattan plot of the GWAS analysis of Chinese individuals.Supplementary Figure 4 Quantile–quantile plot of the Chinese and PGC2 GWAS meta-analysis.Supplementary Figure 5 Manhattan plot of the Chinese and PGC2 GWAS meta-analysis.Supplementary Figure 6 Regional plots of the GWS loci from the Chinese GWAS and replication meta-analysis.Supplementary Figure 7 Fine-mapping analyses for GWS loci nos. The personal and clinical utility of polygenic risk scores.Gronberg, H. et al. Assessment of high-sensitivity C-reactive protein levels as diagnostic discriminator of maturity-onset diabetes of the young due to HNF1A mutations.Thanabalasingham, G. et al. The authors of a controversial new book on Gandhi's life and work in South Africa certainly believe so. Large-scale whole-genome sequencing of the Icelandic population.Huang, J. et al. A meta-analysis of 120 246 individuals identifies 18 new loci for fibrinogen concentration.Ma, J., Xiong, M., You, M., Lozano, G. & Amos, C. I. Genome-wide association tests of inversions with application to psoriasis.Reich, D. et al. & Molteni, R. Synaptic alterations associated with depression and schizophrenia: potential as a therapeutic target.Koide, T. et al.

Genome-wide association study for early-onset and morbid adult obesity identifies three new risk loci in European populations.Berndt, S. I. et al. b The LD results were based on the 1000Genome Project (European or Chinese samples).

going to give away the interpretation based on just one study with no independent replication and with what we now know to be dodgy data (actually I think that we knew the very next day that it was dodgy didn't we, via Guardian and Jeff Barrett?

Comparing CNV detection methods for SNP arrays.Coin, L. J. et al. Then, I got a Kindle Fire (see this discussion), and that was nice. And if there are no common fundamental interests, then the United States and Germany are simply competitors in many areas. Genome-wide association study of exercise behavior in Dutch and American adults.Lane, J. M. et al. Prominent criticisms include concerns that GWAS will eventually implicate the entire genome in disease predisposition and that most association signals reflect variants and genes with no direct biological relevance to disease. researched the literature. & King, M. C. Genetic heterogeneity in human disease.Boyle, E. A., Li, Y. I. et al. Causal and synthetic associations of variants in the SERPINA gene cluster with α1-antitrypsin serum levels.Wray, N. R., Purcell, S. M. & Visscher, P. M. Synthetic associations created by rare variants do not explain most GWAS results.Scherag, A. et al. i see. & Garcia-Closas, M. Developing and evaluating polygenic risk prediction models for stratified disease prevention.Scott, R. A. et al. Systematic identification of trans eQTLs as putative drivers of known disease associations.Fromer, M. et al. Genetic studies of body mass index yield new insights for obesity biology.Müller, M. J. et al. The impact of genotype frequencies on the clinical validity of genomic profiling for predicting common chronic diseases.Stutzmann, F. et al. And Trump keeps repeating it.The discussion becomes almost anecdotal. Thank you for visiting nature.com. Contrasting the genetic architecture of 30 complex traits from summary association data.Bulik-Sullivan, B. K. et al. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.The individual-level genotype and phenotype data are available through formal application to the UK Biobank (http://www.ukbiobank.ac.uk).Thank you for your interest in spreading the word about medRxiv.NOTE: Your email address is requested solely to identify you as the sender of this article.The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.Enter multiple addresses on separate lines or separate them with commas.This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.Genome-wide analyses of behavioural traits biased by misreports and longitudinal changes,Endocrinology (including Diabetes Mellitus and Metabolic Disease),Intensive Care and Critical Care Medicine,Rehabilitation Medicine and Physical Therapy.

Annotation of functional variation in personal genomes using RegulomeDB.Ward, L. D. & Kellis, M. HaploReg v4: systematic mining of putative causal variants, cell types, regulators and target genes for human complex traits and disease.Ward, L. D. & Kellis, M. HaploReg: a resource for exploring chromatin states, conservation, and regulatory motif alterations within sets of genetically linked variants.Gallagher, M. D. & Chen-Plotkin, A. S. The post-GWAS era: from association to function.Denker, A. Genome-wide association studies for complex traits: consensus, uncertainty and challenges.Edwards, S. L., Beesley, J., French, J. D. & Dunning, A. M. Beyond GWASs: illuminating the dark road from association to function.Stryjecki, C., Alyass, A.