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10.1093/bioinformatics/btw270 http://scihub22266oqcxt.onion/10.1093/bioinformatics/btw270 C4908354!4908354!27307613     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Bioinformatics 2016 ; 32 (12): i164-73 Nephropedia Template TP {{tp|p=27307613|t=2016. A network-driven approach for genome-wide association mapping |pdf=|usr=}}{{27307613}} gab.com Text A network-driven approach for genome-wide association mapping JO: Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=27307613 #FOAvip Motivation: It remains a challenge to detect associations between genotypes and phenotypes because of insufficient sample sizes and complex underlying mechanisms involved in associations. Fortunately, it is becoming more feasible to obtain gene expression data in addition to genotypes and phenotypes, giving us new opportunities to detect true genotype?phenotype associations while unveiling their association mechanisms.Results: In this article, we propose a novel method, NETAM, that accurately detects associations between SNPs and phenotypes, as well as gene traits involved in such associations. We take a network-driven approach: NETAM first constructs an association network, where nodes represent SNPs, gene traits or phenotypes, and edges represent the strength of association between two nodes. NETAM assigns a score to each path from an SNP to a phenotype, and then identifies significant paths based on the scores. In our simulation study, we show that NETAM finds significantly more phenotype-associated SNPs than traditional genotype?phenotype association analysis under false positive control, taking advantage of gene expression data. Furthermore, we applied NETAM on late-onset Alzheimer?s disease data and identified 477 significant path associations, among which we analyzed paths related to beta-amyloid, estrogen, and nicotine pathways. We also provide hypothetical biological pathways to explain our findings.Availability and implementation: Software is available at http://www.sailing.cs.cmu.edu/.Contact: epxing@cs.cmu.edu Twit Text FOAVip A network-driven approach for genome-wide association mapping ????Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=27307613 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27307613 #FOAvip English Wikipedia <ref>{{Cite pmid|27307613}}</ref> A network-driven approach for genome-wide association mapping #MMPMID27307613 Lee S; Kong S; Xing EP Bioinformatics 2016[Jun]; 32 (12): i164-73 PMID27307613show ga Motivation: It remains a challenge to detect associations between genotypes and phenotypes because of insufficient sample sizes and complex underlying mechanisms involved in associations. Fortunately, it is becoming more feasible to obtain gene expression data in addition to genotypes and phenotypes, giving us new opportunities to detect true genotype?phenotype associations while unveiling their association mechanisms.Results: In this article, we propose a novel method, NETAM, that accurately detects associations between SNPs and phenotypes, as well as gene traits involved in such associations. We take a network-driven approach: NETAM first constructs an association network, where nodes represent SNPs, gene traits or phenotypes, and edges represent the strength of association between two nodes. NETAM assigns a score to each path from an SNP to a phenotype, and then identifies significant paths based on the scores. In our simulation study, we show that NETAM finds significantly more phenotype-associated SNPs than traditional genotype?phenotype association analysis under false positive control, taking advantage of gene expression data. Furthermore, we applied NETAM on late-onset Alzheimer?s disease data and identified 477 significant path associations, among which we analyzed paths related to beta-amyloid, estrogen, and nicotine pathways. We also provide hypothetical biological pathways to explain our findings.Availability and implementation: Software is available at http://www.sailing.cs.cmu.edu/.Contact: epxing@cs.cmu.edu äA network-driven approach for genome-wide association mapping (epmc).pdf DeepDyve Pubget Overpricing