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本文引用的文献

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RIPSeeker: a statistical package for identifying protein-associated transcripts from RIP-seq experiments.RIPSeeker:一种从 RIP-seq 实验中识别蛋白相关转录本的统计软件包。
Nucleic Acids Res. 2013 Apr;41(8):e94. doi: 10.1093/nar/gkt142. Epub 2013 Feb 28.
2
CLIP-seq of eIF4AIII reveals transcriptome-wide mapping of the human exon junction complex.CLIP-seq 分析 eIF4AIII 揭示了人类外显子连接复合物的转录组范围图谱。
Nat Struct Mol Biol. 2012 Nov;19(11):1124-31. doi: 10.1038/nsmb.2420. Epub 2012 Oct 21.
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The cellular EJC interactome reveals higher-order mRNP structure and an EJC-SR protein nexus.细胞 EJC 相互作用组揭示了更高阶的 mRNP 结构和 EJC-SR 蛋白连接。
Cell. 2012 Nov 9;151(4):750-764. doi: 10.1016/j.cell.2012.10.007. Epub 2012 Oct 18.
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Site identification in high-throughput RNA-protein interaction data.高通量 RNA-蛋白质相互作用数据中的位点鉴定。
Bioinformatics. 2012 Dec 1;28(23):3013-20. doi: 10.1093/bioinformatics/bts569. Epub 2012 Sep 28.
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Protein-RNA interactions: new genomic technologies and perspectives.蛋白质与 RNA 的相互作用:新的基因组技术和展望。
Nat Rev Genet. 2012 Jan 18;13(2):77-83. doi: 10.1038/nrg3141.
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ZINBA integrates local covariates with DNA-seq data to identify broad and narrow regions of enrichment, even within amplified genomic regions.ZINBA 将局部协变量与 DNA 测序数据相结合,以识别广泛和狭窄的富集区域,即使在扩增的基因组区域内也是如此。
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Identification of novel transcripts in annotated genomes using RNA-Seq.利用 RNA-Seq 鉴定注释基因组中的新型转录本。
Bioinformatics. 2011 Sep 1;27(17):2325-9. doi: 10.1093/bioinformatics/btr355. Epub 2011 Jun 21.
8
A quantitative analysis of CLIP methods for identifying binding sites of RNA-binding proteins.CLIP 方法识别 RNA 结合蛋白结合位点的定量分析。
Nat Methods. 2011 May 15;8(7):559-64. doi: 10.1038/nmeth.1608.
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PeakSeq enables systematic scoring of ChIP-seq experiments relative to controls.PeakSeq能够相对于对照对ChIP-seq实验进行系统评分。
Nat Biotechnol. 2009 Jan;27(1):66-75. doi: 10.1038/nbt.1518. Epub 2009 Jan 4.
10
An integrated software system for analyzing ChIP-chip and ChIP-seq data.一个用于分析染色质免疫沉淀芯片(ChIP-chip)和染色质免疫沉淀测序(ChIP-seq)数据的集成软件系统。
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ASPeak:一种用于 RIP-Seq 的丰度敏感峰检测算法。

ASPeak: an abundance sensitive peak detection algorithm for RIP-Seq.

机构信息

Department of Biochemistry and Molecular Pharmacology, Howard Hughes Medical Institute, University of Massachusetts Medical School, Worcester, MA 01605 and Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.

出版信息

Bioinformatics. 2013 Oct 1;29(19):2485-6. doi: 10.1093/bioinformatics/btt428. Epub 2013 Aug 8.

DOI:10.1093/bioinformatics/btt428
PMID:23929032
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3777114/
Abstract

SUMMARY

Unlike DNA, RNA abundances can vary over several orders of magnitude. Thus, identification of RNA-protein binding sites from high-throughput sequencing data presents unique challenges. Although peak identification in ChIP-Seq data has been extensively explored, there are few bioinformatics tools tailored for peak calling on analogous datasets for RNA-binding proteins. Here we describe ASPeak (abundance sensitive peak detection algorithm), an implementation of an algorithm that we previously applied to detect peaks in exon junction complex RNA immunoprecipitation in tandem experiments. Our peak detection algorithm yields stringent and robust target sets enabling sensitive motif finding and downstream functional analyses.

AVAILABILITY

ASPeak is implemented in Perl as a complete pipeline that takes bedGraph files as input. ASPeak implementation is freely available at https://sourceforge.net/projects/as-peak under the GNU General Public License. ASPeak can be run on a personal computer, yet is designed to be easily parallelizable. ASPeak can also run on high performance computing clusters providing efficient speedup. The documentation and user manual can be obtained from http://master.dl.sourceforge.net/project/as-peak/manual.pdf.

摘要

摘要

与 DNA 不同,RNA 的丰度可以变化几个数量级。因此,从高通量测序数据中识别 RNA-蛋白质结合位点提出了独特的挑战。尽管 ChIP-Seq 数据中的峰识别已经得到了广泛的研究,但针对 RNA 结合蛋白的类似数据集的峰调用,生物信息学工具还很少。在这里,我们描述了 ASPeak(丰度敏感峰检测算法),这是我们之前应用于串联实验中外显子连接复合物 RNA 免疫沉淀中检测峰的算法的实现。我们的峰检测算法产生了严格而稳健的目标集,能够进行敏感的基序发现和下游功能分析。

可用性

ASPeak 是用 Perl 实现的,作为一个完整的管道,以 bedGraph 文件作为输入。ASPeak 的实现可在 https://sourceforge.net/projects/as-peak 下根据 GNU 通用公共许可证免费获得。ASPeak 可以在个人计算机上运行,但设计为易于并行化。ASPeak 也可以在高性能计算集群上运行,提供高效的加速。文档和用户手册可从 http://master.dl.sourceforge.net/project/as-peak/manual.pdf 获得。