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10.1515/sagmb-2012-0057 http://scihub22266oqcxt.onion/10.1515/sagmb-2012-0057 C4866591!4866591!23502341     free     free     free Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Stat+Appl+Genet+Mol+Biol 2013 ; 12 (2): 189-205 Nephropedia Template TP {{tp|p=23502341|t=2013. Detection of Epigenetic Changes Using ANOVA with Spatially Varying Coefficients |pdf=|usr=}}{{23502341}} gab.com Text Detection of Epigenetic Changes Using ANOVA with Spatially Varying Coefficients JO: Stat Appl Genet Mol Biol http://www.kidney.de/pget.php?&tw=1&pmid=23502341 #FOAvip Identification of genome-wide epigenetic changes, the stable changes in gene function without a change in DNA sequence, under various conditions plays an important role in biomedical research. High-throughput epigenetic experiments are useful tools to measure genome-wide epigenetic changes, but the measured intensity levels from these high-resolution genome-wide epigenetic profiling data are often spatially correlated with high noise levels. In addition, no formal statistical method was developed to compare genome-wide epigenetic changes across multiple conditions. In this study, we consider ANOVA models with spatially varying coefficients, combined with a hierarchical Bayes approach, to explicitly model spatial correlation caused by location-dependent biological effects (i.e., epigenetic changes) and borrow strength among neighboring probes to compare epigenetic changes across multiple conditions. Through simulation studies and applications in drug addiction and depression models, we find that our approach compares favorably with competing methods; it is more efficient in estimation and more effective in detecting epigenetic changes. In addition, it can provide biologically meaningful results. Twit Text FOAVip Detection of Epigenetic Changes Using ANOVA with Spatially Varying Coefficients ????Stat Appl Genet Mol Biol http://www.kidney.de/pget.php?&tw=1&pmid=23502341 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=23502341 #FOAvip English Wikipedia <ref>{{Cite pmid|23502341}}</ref> Detection of Epigenetic Changes Using ANOVA with Spatially Varying Coefficients #MMPMID23502341 Xiao G; Wang X; LaPlant Q; Nestler E; Xie Y Stat Appl Genet Mol Biol 2013[May]; 12 (2): 189-205 PMID23502341show ga Identification of genome-wide epigenetic changes, the stable changes in gene function without a change in DNA sequence, under various conditions plays an important role in biomedical research. High-throughput epigenetic experiments are useful tools to measure genome-wide epigenetic changes, but the measured intensity levels from these high-resolution genome-wide epigenetic profiling data are often spatially correlated with high noise levels. In addition, no formal statistical method was developed to compare genome-wide epigenetic changes across multiple conditions. In this study, we consider ANOVA models with spatially varying coefficients, combined with a hierarchical Bayes approach, to explicitly model spatial correlation caused by location-dependent biological effects (i.e., epigenetic changes) and borrow strength among neighboring probes to compare epigenetic changes across multiple conditions. Through simulation studies and applications in drug addiction and depression models, we find that our approach compares favorably with competing methods; it is more efficient in estimation and more effective in detecting epigenetic changes. In addition, it can provide biologically meaningful results. äDetection of Epigenetic Changes Using ANOVA with Spatially Varying Coe(epmc).pdf DeepDyve Pubget Overpricing