Package: QNB
Type: Package
Title: Differential RNA Methylation Analysis for Count-Based
        Small-Sample Sequencing Data with a Quad-Negative Binomial
        Model
Version: 1.1.2
Date: 2016-12-25
Author: Lian Liu <liulian19860905@163.com>
Maintainer: Lian Liu <liulian19860905@163.com>
Description: As a newly emerged research area, RNA epigenetics has drawn increasing 
             attention recently for the participation of RNA methylation and other 
             modifications in a number of crucial biological processes. Thanks to high 
             throughput sequencing techniques, such as m6A-Seq, transcriptome-wide RNA 
             methylation profile is now available in the form of count-based data, with 
             which it is often of interests to study the dynamics in epitranscriptomic 
             layer. However, the sample size of RNA methylation experiment is usually 
             very small due to its costs; and additionally, there usually exist a large 
             number of genes whose methylation level cannot be accurately estimated due 
             to their low expression level, making differential RNA methylation analysis 
             a difficult task.
             We present QNB, a statistical approach for differential RNA methylation 
             analysis with count-based small-sample sequencing data. The method is based 
             on 4 independent negative binomial dis-tributions with their variances and 
             means linked by local regressions. QNB showed improved performance on 
             simulated and real m6A-Seq datasets when compared with competing algorithms. 
             And the QNB model is also applicable to other datasets related RNA 
             modifications, including but not limited to RNA bisulfite sequencing, 
             m1A-Seq, Par-CLIP, RIP-Seq, etc.Please don't hesitate to contact 
            <liulian19860905@163.com> if you have any questions.
License: GPL-2
Depends: locfit
Packaged: 2016-12-28 02:37:40 UTC; S41-70
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2016-12-28 17:54:21
