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10.1158/1055-9965.EPI-16-0106 http://scihub22266oqcxt.onion/10.1158/1055-9965.EPI-16-0106 C5224974!5224974!27697780     free     free     free Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Cancer+Epidemiol+Biomarkers+Prev 2017 ; 26 (1): 126-35 Nephropedia Template TP {{tp|p=27697780|t=2017. The OncoArray Consortium: a Network for Understanding the Genetic Architecture of Common Cancers |pdf=|usr=}}{{27697780}} gab.com Text The OncoArray Consortium: a Network for Understanding the Genetic Architecture of Common Cancers JO: Cancer Epidemiol Biomarkers Prev http://www.kidney.de/pget.php?&tw=1&pmid=27697780 #FOAvip Background: Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers and cancer related traits. Methods: The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background. Results: The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis. Conclusions: Results from these analyses will enable researchers to identify new susceptibility loci, perform fine mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental and lifestyle related exposures. Impact: Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. Twit Text FOAVip The OncoArray Consortium: a Network for Understanding the Genetic Architecture of Common Cancers ????Cancer Epidemiol Biomarkers Prev http://www.kidney.de/pget.php?&tw=1&pmid=27697780 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27697780 #FOAvip English Wikipedia <ref>{{Cite pmid|27697780}}</ref> The OncoArray Consortium: a Network for Understanding the Genetic Architecture of Common Cancers #MMPMID27697780 Amos CI; Dennis J; Wang Z; Byun J; Schumacher FR; Gayther SA; Casey G; Hunter DJ; Sellers TA; Gruber SB; Dunning AM; Michailidou K; Fachal L; Doheny K; Spurdle AB; Li Y; Xiao X; Romm J; Pugh E; Coetzee GA; Hazelett DJ; Bojesen SE; Caga-Anan C; Haiman CA; Kamal A; Luccarini C; Tessier D; Vincent D; Bacot F; Van Den Berg DJ; Nelson S; Demetriades S; Goldgar DE; Couch FJ; Forman JL; Giles GG; Conti DV; Bickeböller H; Risch A; Waldenberger M; Brüske I; Hicks BD; Ling H; McGuffog L; Lee A; Kuchenbaecker KB; Soucy P; Manz J; Cunningham JM; Butterbach K; Kote-Jarai Z; Kraft P; FitzGerald LM; Lindström S; Adams M; McKay JD; Phelan CM; Benlloch S; Kelemen LE; Brennan P; Riggan M; O?Mara TA; Shen H; Shi Y; Thompson DJ; Goodman MT; Nielsen SF; Berchuck A; Laboissiere S; Schmit SL; Shelford T; Edlund CK; Taylor JA; Field JK; Park SK; Offit K; Thomassen M; Schmutzler R; Ottini L; Hung RJ; Marchini J; Al Olama AA; Peters U; Eeles RA; Seldin MF; Gillanders E; Seminara D; Antoniou AC; Pharoah PD; Chenevix-Trench G; Chanock SJ; Simard J; Easton DF Cancer Epidemiol Biomarkers Prev 2017[Jan]; 26 (1): 126-35 PMID27697780show ga Background: Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers and cancer related traits. Methods: The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background. Results: The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis. Conclusions: Results from these analyses will enable researchers to identify new susceptibility loci, perform fine mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental and lifestyle related exposures. Impact: Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. äThe OncoArray Consortium: a Network for Understanding the Genetic Arch(epmc).pdf DeepDyve Pubget Overpricing