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10.1371/journal.pgen.1007240 http://scihub22266oqcxt.onion/10.1371/journal.pgen.1007240 C5843356!5843356!29481575     free     free     free Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       PLoS+Genet 2018 ; 14 (2): ä Nephropedia Template TP {{tp|p=29481575|t=2018. Methods for fine-mapping with chromatin and expression data |pdf=|usr=}}{{29481575}} gab.com Text Methods for fine-mapping with chromatin and expression data JO: PLoS Genet http://www.kidney.de/pget.php?&tw=1&pmid=29481575 #FOAvip Recent studies have identified thousands of regions in the genome associated with chromatin modifications, which may in turn be affecting gene expression. Existing works have used heuristic methods to investigate the relationships between genome, epigenome, and gene expression, but, to our knowledge, none have explicitly modeled the chain of causality whereby genetic variants impact chromatin, which impacts gene expression. In this work we introduce a new hierarchical fine-mapping framework that integrates information across all three levels of data to better identify the causal variant and chromatin mark that are concordantly influencing gene expression. In simulations we show that our method is more accurate than existing approaches at identifying the causal mark influencing expression. We analyze empirical genetic, chromatin, and gene expression data from 65 African-ancestry and 47 European-ancestry individuals and show that many of the paths prioritized by our method are consistent with the proposed causal model and often lie in likely functional regions. Twit Text FOAVip Methods for fine-mapping with chromatin and expression data ????PLoS Genet http://www.kidney.de/pget.php?&tw=1&pmid=29481575 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=29481575 #FOAvip English Wikipedia <ref>{{Cite pmid|29481575}}</ref> Methods for fine-mapping with chromatin and expression data #MMPMID29481575 Roytman M; Kichaev G; Gusev A; Pasaniuc B PLoS Genet 2018[Feb]; 14 (2): ä PMID29481575show ga Recent studies have identified thousands of regions in the genome associated with chromatin modifications, which may in turn be affecting gene expression. Existing works have used heuristic methods to investigate the relationships between genome, epigenome, and gene expression, but, to our knowledge, none have explicitly modeled the chain of causality whereby genetic variants impact chromatin, which impacts gene expression. In this work we introduce a new hierarchical fine-mapping framework that integrates information across all three levels of data to better identify the causal variant and chromatin mark that are concordantly influencing gene expression. In simulations we show that our method is more accurate than existing approaches at identifying the causal mark influencing expression. We analyze empirical genetic, chromatin, and gene expression data from 65 African-ancestry and 47 European-ancestry individuals and show that many of the paths prioritized by our method are consistent with the proposed causal model and often lie in likely functional regions. äMethods for fine-mapping with chromatin and expression data (epmc).pdf DeepDyve Pubget Overpricing