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混合模型和小波变换揭示了 MOV10 PAR-CLIP 数据中高可信度的 RNA-蛋白质相互作用位点。

Mixture models and wavelet transforms reveal high confidence RNA-protein interaction sites in MOV10 PAR-CLIP data.

机构信息

Department of Biosystems Science and Engineering, Swiss Federal Institute of Technology Zurich, Mattenstrasse 26, 4058 Basel, Switzerland.

出版信息

Nucleic Acids Res. 2012 Nov 1;40(20):e160. doi: 10.1093/nar/gks697. Epub 2012 Jul 28.

DOI:10.1093/nar/gks697
PMID:22844102
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3488208/
Abstract

The Photo-Activatable Ribonucleoside-enhanced CrossLinking and ImmunoPrecipitation (PAR-CLIP) method was recently developed for global identification of RNAs interacting with proteins. The strength of this versatile method results from induction of specific T to C transitions at sites of interaction. However, current analytical tools do not distinguish between non-experimentally and experimentally induced transitions. Furthermore, geometric properties at potential binding sites are not taken into account. To surmount these shortcomings, we developed a two-step algorithm consisting of a non-parametric two-component mixture model and a wavelet-based peak calling procedure. Our algorithm can reduce the number of false positives up to 24% thereby identifying high confidence interaction sites. We successfully employed this approach in conjunction with a modified PAR-CLIP protocol to study the functional role of nuclear Moloney leukemia virus 10, a putative RNA helicase interacting with Argonaute2 and Polycomb. Our method, available as the R package wavClusteR, is generally applicable to any substitution-based inference problem in genomics.

摘要

光激活核苷酸增强交联和免疫沉淀(PAR-CLIP)方法最近被开发用于全局鉴定与蛋白质相互作用的 RNA。该多功能方法的优势在于在相互作用位点诱导特定的 T 到 C 转换。然而,当前的分析工具无法区分非实验和实验诱导的转换。此外,潜在结合位点的几何性质也未被考虑在内。为了克服这些缺点,我们开发了一种由非参数两分量混合模型和基于小波的峰调用程序组成的两步算法。我们的算法可以将假阳性数量减少多达 24%,从而识别出高可信度的相互作用位点。我们成功地将这种方法与改良的 PAR-CLIP 协议结合使用,以研究核 Moloney 白血病病毒 10 的功能作用,这是一种与 Argonaute2 和 Polycomb 相互作用的假定 RNA 解旋酶。我们的方法,作为 R 包 wavClusteR 提供,通常适用于基因组学中任何基于替换的推断问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65df/3488208/72ea9fd1b4f2/gks697f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65df/3488208/e220f03d55f7/gks697f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65df/3488208/593b13c50d54/gks697f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65df/3488208/9087ab111173/gks697f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65df/3488208/72ea9fd1b4f2/gks697f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65df/3488208/e220f03d55f7/gks697f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65df/3488208/593b13c50d54/gks697f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65df/3488208/9087ab111173/gks697f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65df/3488208/72ea9fd1b4f2/gks697f4.jpg

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