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10.1155/2016/2615348 http://scihub22266oqcxt.onion/10.1155/2016/2615348 C4808532!4808532!27034928     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Biomed+Res+Int 2016 ; 2016 (ä): ä Nephropedia Template TP {{tp|p=27034928|t=2016. An Efficient Approach to Screening Epigenome-Wide Data |pdf=|usr=}}{{27034928}} gab.com Text An Efficient Approach to Screening Epigenome-Wide Data JO: Biomed Res Int http://www.kidney.de/pget.php?&tw=1&pmid=27034928 #FOAvip Screening cytosine-phosphate-guanine dinucleotide (CpG) DNA methylation sites in association with some covariate(s) is desired due to high dimensionality. We incorporate surrogate variable analyses (SVAs) into (ordinary or robust) linear regressions and utilize training and testing samples for nested validation to screen CpG sites. SVA is to account for variations in the methylation not explained by the specified covariate(s) and adjust for confounding effects. To make it easier to users, this screening method is built into a user-friendly R package, ttScreening, with efficient algorithms implemented. Various simulations were implemented to examine the robustness and sensitivity of the method compared to the classical approaches controlling for multiple testing: the false discovery rates-based (FDR-based) and the Bonferroni-based methods. The proposed approach in general performs better and has the potential to control both types I and II errors. We applied ttScreening to 383,998 CpG sites in association with maternal smoking, one of the leading factors for cancer risk. Twit Text FOAVip An Efficient Approach to Screening Epigenome-Wide Data ????Biomed Res Int http://www.kidney.de/pget.php?&tw=1&pmid=27034928 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27034928 #FOAvip English Wikipedia <ref>{{Cite pmid|27034928}}</ref> An Efficient Approach to Screening Epigenome-Wide Data #MMPMID27034928 Ray MA; Tong X; Lockett GA; Zhang H; Karmaus WJJ Biomed Res Int 2016[]; 2016 (ä): ä PMID27034928show ga Screening cytosine-phosphate-guanine dinucleotide (CpG) DNA methylation sites in association with some covariate(s) is desired due to high dimensionality. We incorporate surrogate variable analyses (SVAs) into (ordinary or robust) linear regressions and utilize training and testing samples for nested validation to screen CpG sites. SVA is to account for variations in the methylation not explained by the specified covariate(s) and adjust for confounding effects. To make it easier to users, this screening method is built into a user-friendly R package, ttScreening, with efficient algorithms implemented. Various simulations were implemented to examine the robustness and sensitivity of the method compared to the classical approaches controlling for multiple testing: the false discovery rates-based (FDR-based) and the Bonferroni-based methods. The proposed approach in general performs better and has the potential to control both types I and II errors. We applied ttScreening to 383,998 CpG sites in association with maternal smoking, one of the leading factors for cancer risk. äAn Efficient Approach to Screening Epigenome-Wide Data (epmc).pdf DeepDyve Pubget Overpricing