Computational analysis of small RNA cloning data
Computational analysis of small RNA cloning data
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DOI：
10.1016/j.ymeth.2007.10.002
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发表时间：
2008-01-01
期刊：
影响因子：
4.8
通讯作者：
Zavolan, Mihaela
中科院分区：
文献类型：
--
作者：
Berninger, Philipp;Gaidatzis, Dimos;Zavolan, Mihaela
克隆和测序是鉴定小调控RNA的首选方法。使用深度测序技术，人们现在可以从一个文库中获得多达10亿个核苷酸和数千万个小RNA。对这些文库的仔细计算分析使得能够发现miRNA、rasiRNA、piRNA和21 U RNA。鉴于可以从每个个体样本中获得大量序列，深度测序可能很快成为寡核苷酸微阵列技术用于mRNA表达谱分析的替代方案。在这份报告中，我们提出的方法，我们开发的注释和表达谱的小RNA通过大规模测序。其中包括一个快速算法，用于在序列数据库中找到几乎完美匹配的小RNA，一个网络访问的软件系统，用于注释小RNA文库，以及一个贝叶斯方法，用于比较小RNA表达的样品。(c)2007爱思唯尔公司All rights reserved.
Cloning and sequencing is the method of choice for small regulatory RNA identification. Using deep sequencing technologies one can now obtain up to a billion nucleotides - and tens of millions of small RNAs-from a single library. Careful computational analyses of such libraries enabled the discovery of miRNAs, rasiRNAs, piRNAs, and 21 U RNAs. Given the large number of sequences that can be obtained from each individual sample, deep sequencing may soon become an alternative to oligonucleotide microarray technology for mRNA expression profiling. In this report we present the methods that we developed for the annotation and expression profiling of small RNAs obtained through large-scale sequencing. These include a fast algorithm for finding nearly perfect matches of small RNAs in sequence databases, a web-accessible software system for the annotation of small RNA libraries, and a Bayesian method for comparing small RNA expression across samples. (c) 2007 Elsevier Inc. All rights reserved.