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10.1177/0962280211428386 http://scihub22266oqcxt.onion/10.1177/0962280211428386 C4605138!4605138!22127579     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\22127579.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Stat+Methods+Med+Res 2013 ; 22 (5): 519-36 Nephropedia Template TP {{tp|p=22127579|t=2013. Finding consistent patterns: A nonparametric approach for identifying differential expression in RNA-Seq data |pdf=|usr=}}{{22127579}} gab.com Text Finding consistent patterns: A nonparametric approach for identifying differential expression in RNA-Seq data JO: Stat Methods Med Res http://www.kidney.de/pget.php?&tw=1&pmid=22127579 #FOAvip We discuss the identification of features that are associated with an outcome in RNA-Sequencing (RNA-Seq) and other sequencing-based comparative genomic experiments. RNA-Seq data takes the form of counts, so models based on the normal distribution are generally unsuitable. The problem is especially challenging because different sequencing experiments may generate quite different total numbers of reads, or ?sequencing depths?. Existing methods for this problem are based on Poisson or negative binomial models: they are useful but can be heavily influenced by ?outliers? in the data. We introduce a simple, nonparametric method with resampling to account for the different sequencing depths. The new method is more robust than parametric methods. It can be applied to data with quantitative, survival, two-class or multiple-class outcomes. We compare our proposed method to Poisson and negative binomial-based methods in simulated and real data sets, and find that our method discovers more consistent patterns than competing methods. Twit Text FOAVip Finding consistent patterns: A nonparametric approach for identifying differential expression in RNA-Seq data ????Stat Methods Med Res http://www.kidney.de/pget.php?&tw=1&pmid=22127579 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=22127579 #FOAvip English Wikipedia <ref>{{Cite pmid|22127579}}</ref> Finding consistent patterns: A nonparametric approach for identifying differential expression in RNA-Seq data #MMPMID22127579 Li J; Tibshirani R Stat Methods Med Res 2013[Oct]; 22 (5): 519-36 PMID22127579show ga We discuss the identification of features that are associated with an outcome in RNA-Sequencing (RNA-Seq) and other sequencing-based comparative genomic experiments. RNA-Seq data takes the form of counts, so models based on the normal distribution are generally unsuitable. The problem is especially challenging because different sequencing experiments may generate quite different total numbers of reads, or ?sequencing depths?. Existing methods for this problem are based on Poisson or negative binomial models: they are useful but can be heavily influenced by ?outliers? in the data. We introduce a simple, nonparametric method with resampling to account for the different sequencing depths. The new method is more robust than parametric methods. It can be applied to data with quantitative, survival, two-class or multiple-class outcomes. We compare our proposed method to Poisson and negative binomial-based methods in simulated and real data sets, and find that our method discovers more consistent patterns than competing methods. äFinding consistent patterns: A nonparametric approach for identifying (epmc).pdf DeepDyve Pubget Overpricing