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.

10.1186/s12859-016-0961-5 http://scihub22266oqcxt.onion/10.1186/s12859-016-0961-5 C4782413!4782413!26951498     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       BMC+Bioinformatics 2016 ; 17 (ä): ä Nephropedia Template TP {{tp|p=26951498|t=2016. Testing for association between RNA-Seq and high-dimensional data |pdf=|usr=}}{{26951498}} gab.com Text Testing for association between RNA-Seq and high-dimensional data JO: BMC Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=26951498 #FOAvip Background: Testing for association between RNA-Seq and other genomic data is challenging due to high variability of the former and high dimensionality of the latter. Results: Using the negative binomial distribution and a random-effects model, we develop an omnibus test that overcomes both difficulties. It may be conceptualised as a test of overall significance in regression analysis, where the response variable is overdispersed and the number of explanatory variables exceeds the sample size. Conclusions: The proposed test can detect genetic and epigenetic alterations that affect gene expression. It can examine complex regulatory mechanisms of gene expression. The R package globalSeq is available from Bioconductor. Electronic supplementary material: The online version of this article (doi:10.1186/s12859-016-0961-5) contains supplementary material, which is available to authorized users. Twit Text FOAVip Testing for association between RNA-Seq and high-dimensional data ????BMC Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=26951498 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26951498 #FOAvip English Wikipedia <ref>{{Cite pmid|26951498}}</ref> Testing for association between RNA-Seq and high-dimensional data #MMPMID26951498 Rauschenberger A; Jonker MA; van de Wiel MA; Menezes RX BMC Bioinformatics 2016[]; 17 (ä): ä PMID26951498show ga Background: Testing for association between RNA-Seq and other genomic data is challenging due to high variability of the former and high dimensionality of the latter. Results: Using the negative binomial distribution and a random-effects model, we develop an omnibus test that overcomes both difficulties. It may be conceptualised as a test of overall significance in regression analysis, where the response variable is overdispersed and the number of explanatory variables exceeds the sample size. Conclusions: The proposed test can detect genetic and epigenetic alterations that affect gene expression. It can examine complex regulatory mechanisms of gene expression. The R package globalSeq is available from Bioconductor. Electronic supplementary material: The online version of this article (doi:10.1186/s12859-016-0961-5) contains supplementary material, which is available to authorized users. äTesting for association between RNA-Seq and high-dimensional data (epmc).pdf DeepDyve Pubget Overpricing