RIPSeeker: a statistical package for identifying protein-associated transcripts from RIP-seq experiments.
RIPSeeker: a statistical package for identifying protein-associated transcripts from RIP-seq experiments.
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DOI：
10.1093/nar/gkt142
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发表时间：
2013-04
影响因子：
14.9
通讯作者：
Zhang Z
中科院分区：
文献类型：
--
作者：
Li Y;Zhao DY;Greenblatt JF;Zhang Z
RIP-seq最近被用于发现与蛋白质或蛋白质复合物相互作用的全基因组RNA转录本。RIP-seq与RNA-seq和ChIP-seq相似，但具有独特的性质和挑战。目前，还没有专门用于RIP-seq分析的统计工具。我们开发了RIPSeeker (http://www.bioconductor.org/packages/2.12/bioc/html/RIPSeeker.html)，这是一个免费的开源Bioconductor/R包，用于基于HMM的从头RIP峰值预测。为了证明该软件包的实用性，我们将RIPSeeker和其他六个已发布的程序应用于三个独立的RIP-seq数据集和两个PAR-CLIP数据集，这些数据集对应于六个不同的rna结合蛋白。基于受体工作曲线，RIPSeeker在区分高置信峰方面表现出卓越的灵敏度和特异性，在大多数比较方法中一致同意，并且在12次评价中占主导地位，平均曲线下面积为80%。来自RIPSeeker的峰进一步证实了它们对生物学上有意义的基因组元件的显著富集，已公布的序列基序以及与已知与所检测蛋白质相互作用的规范转录本的关联。虽然RIPSeeker是专门为RIP-seq数据分析量身定制的，但它还提供了一套生物信息学工具，集成在一个独立的软件包中，全面解决了从比对后处理到可视化和注释的问题。
RIP-seq has recently been developed to discover genome-wide RNA transcripts that interact with a protein or protein complex. RIP-seq is similar to both RNA-seq and ChIP-seq, but presents unique properties and challenges. Currently, no statistical tool is dedicated to RIP-seq analysis. We developed RIPSeeker (http://www.bioconductor.org/packages/2.12/bioc/html/RIPSeeker.html), a free open-source Bioconductor/R package for de novo RIP peak predictions based on HMM. To demonstrate the utility of the software package, we applied RIPSeeker and six other published programs to three independent RIP-seq datasets and two PAR-CLIP datasets corresponding to six distinct RNA-binding proteins. Based on receiver operating curves, RIPSeeker demonstrates superior sensitivity and specificity in discriminating high-confidence peaks that are consistently agreed on among a majority of the comparison methods, and dominated 9 of the 12 evaluations, averaging 80% area under the curve. The peaks from RIPSeeker are further confirmed based on their significant enrichment for biologically meaningful genomic elements, published sequence motifs and association with canonical transcripts known to interact with the proteins examined. While RIPSeeker is specifically tailored for RIP-seq data analysis, it also provides a suite of bioinformatics tools integrated within a self-contained software package comprehensively addressing issues ranging from post-alignments’ processing to visualization and annotation.
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影响因子：
64.5
作者：
Hafner M;Landthaler M;Burger L;Khorshid M;Hausser J;Berninger P;Rothballer A;Ascano M Jr;Jungkamp AC;Munschauer M;Ulrich A;Wardle GS;Dewell S;Zavolan M;Tuschl T
通讯作者：
Tuschl T
影响因子：
48
作者：
Cloonan, Nicole;Forrest, Alistair R. R.;Grimmond, Sean M.
通讯作者：
Grimmond, Sean M.
影响因子：
11.4
作者：
Huntzinger, Eric;Braun, Joerg E.;Heimstaedt, Susanne;Zekri, Latifa;Izaurralde, Elisa
通讯作者：
Izaurralde, Elisa
DOI：
10.1186/1748-7188-6-26
发表时间：
2011-11-24
期刊：
Algorithms for molecular biology : AMB
影响因子：
--
作者：
Lorenz R;Bernhart SH;Höner Zu Siederdissen C;Tafer H;Flamm C;Stadler PF;Hofacker IL
通讯作者：
Hofacker IL
DOI：
10.1111/j.2517-6161.1995.tb02031.x
发表时间：
1995-01-01
影响因子：
5.8
作者：
BENJAMINI, Y;HOCHBERG, Y
通讯作者：
HOCHBERG, Y