Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText. Kick-your-searchterm to multiple Engines kick-your-query now !>

A dictionary by aggregated review articles of nephrology, medicine and the life sciences Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

10.1159/000362837 http://scihub22266oqcxt.onion/10.1159/000362837 C4152945!4152945!25096029     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 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Hum+Hered 2014 ; 78 (2): 94-103 Nephropedia Template TP {{tp|p=25096029|t=2014. Using Gene Expression to Improve the Power of Genome-Wide Association Analysis |pdf=|usr=}}{{25096029}} gab.com Text Using Gene Expression to Improve the Power of Genome-Wide Association Analysis JO: Hum Hered http://www.kidney.de/pget.php?&tw=1&pmid=25096029 #FOAvip Motivation: Genome-wide association (GWA) studies have reported susceptible regions in the human genome for many common diseases and traits, however, these loci only explain a minority of trait heritability. To boost the power of a GWA study, substantial research endeavors have been focused on integrating other available genomic information in the analysis. Advances in high through-put technologies have generated a wealth of genomic data, and made combining SNP and gene expression data become feasible. Results: In this paper we propose a novel procedure to incorporate gene expression information into GWA analysis. This procedure utilizes weights constructed by gene expression measurements to adjust p values from a GWA analysis. Results from simulation analyses indicate that the proposed procedures may achieve substantial power gains while controlling family-wise type I error rate (FWER) at the nominal level. To demonstrate the implementation of our proposed approach, we apply the weight adjustment procedure to a GWA study for serum interferon-regulated chemokine levels in systemic lupus erythematosus (SLE) patients. The study results can provide valuable insights for the functional interpretation of GWA signals. Availability: The R source code for implementing the proposed weighting procedure is available at http://www.biostat.umn.edu/~yho/research.html Twit Text FOAVip Using Gene Expression to Improve the Power of Genome-Wide Association Analysis ????Hum Hered http://www.kidney.de/pget.php?&tw=1&pmid=25096029 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=25096029 #FOAvip English Wikipedia <ref>{{Cite pmid|25096029}}</ref> Using Gene Expression to Improve the Power of Genome-Wide Association Analysis #MMPMID25096029 Ho YY; Baechler EC; Ortmann W; Behrens TW; Graham RR; Bhangale TR; Pan W Hum Hered 2014[]; 78 (2): 94-103 PMID25096029show ga Motivation: Genome-wide association (GWA) studies have reported susceptible regions in the human genome for many common diseases and traits, however, these loci only explain a minority of trait heritability. To boost the power of a GWA study, substantial research endeavors have been focused on integrating other available genomic information in the analysis. Advances in high through-put technologies have generated a wealth of genomic data, and made combining SNP and gene expression data become feasible. Results: In this paper we propose a novel procedure to incorporate gene expression information into GWA analysis. This procedure utilizes weights constructed by gene expression measurements to adjust p values from a GWA analysis. Results from simulation analyses indicate that the proposed procedures may achieve substantial power gains while controlling family-wise type I error rate (FWER) at the nominal level. To demonstrate the implementation of our proposed approach, we apply the weight adjustment procedure to a GWA study for serum interferon-regulated chemokine levels in systemic lupus erythematosus (SLE) patients. The study results can provide valuable insights for the functional interpretation of GWA signals. Availability: The R source code for implementing the proposed weighting procedure is available at http://www.biostat.umn.edu/~yho/research.html äUsing Gene Expression to Improve the Power of Genome-Wide Association (epmc).pdf DeepDyve Pubget Overpricing