Janelia Farm Research Campus; Ashburn, VA USA.
RNA Biol. 2013 Jul;10(7):1170-9. doi: 10.4161/rna.25038. Epub 2013 May 20.
A key step toward understanding a metagenomics data set is the identification of functional sequence elements within it, such as protein coding genes and structural RNAs. Relative to protein coding genes, structural RNAs are more difficult to identify because of their reduced alphabet size, lack of open reading frames, and short length. Infernal is a software package that implements "covariance models" (CMs) for RNA homology search, which harness both sequence and structural conservation when searching for RNA homologs. Thanks to the added statistical signal inherent in the secondary structure conservation of many RNA families, Infernal is more powerful than sequence-only based methods such as BLAST and profile HMMs. Together with the Rfam database of CMs, Infernal is a useful tool for identifying RNAs in metagenomics data sets.
理解宏基因组数据集的关键步骤是识别其中的功能序列元素，如蛋白质编码基因和结构 RNA。与蛋白质编码基因相比，由于其字母表尺寸较小、缺乏开放阅读框和长度较短，因此更难识别结构 RNA。Infernal 是一个实现 RNA 同源搜索的“协方差模型”（CM）的软件包，在搜索 RNA 同源物时利用序列和结构的保守性。由于许多 RNA 家族的二级结构保守性所固有的附加统计信号，Infernal 比基于序列的方法（如 BLAST 和轮廓 HMM）更强大。Infernal 与 Rfam CM 数据库一起，是识别宏基因组数据集中 RNA 的有用工具。
