Leung Henry C M, Yiu Siu-Ming, Parkinson John, Chin Francis Y L
Department of Computer Science, The University of Hong Kong, Hong Kong, People's Republic of China.
J Comput Biol. 2013 Jul;20(7):540-50. doi: 10.1089/cmb.2013.0042.
High-throughput next-generation sequencing technology provides a great opportunity for analyzing metatranscriptomic data. However, the reads produced by these technologies are short and an assembling step is required to combine the short reads into longer contigs. As there are many repeat patterns in mRNAs from different genomes and the abundance ratio of mRNAs in a sample varies a lot, existing assemblers for genomic data, transcriptomic data, and metagenomic data do not work on metatranscriptomic data and produce chimeric contigs, that is, incorrect contigs formed by merging multiple mRNA sequences. To our best knowledge, there is no assembler designed for metatranscriptomic data. In this article, we introduce an assembler called IDBA-MT, which is designed for assembling reads from metatranscriptomic data. IDBA-MT produces much fewer chimeric contigs (reduce by 50% or more) when compared with existing assemblers such as Oases, IDBA-UD, and Trinity.
高通量下一代测序技术为分析宏转录组数据提供了绝佳机会。然而，这些技术产生的读段很短，需要一个组装步骤将短读段拼接成更长的重叠群。由于来自不同基因组的mRNA中存在许多重复模式，且样本中mRNA的丰度比差异很大，现有的用于基因组数据、转录组数据和宏基因组数据的组装工具不适用于宏转录组数据，会产生嵌合重叠群，即由多个mRNA序列合并形成的错误重叠群。据我们所知，尚无专门为宏转录组数据设计的组装工具。在本文中，我们介绍了一种名为IDBA-MT的组装工具，它专为组装宏转录组数据的读段而设计。与诸如Oases、IDBA-UD和Trinity等现有组装工具相比，IDBA-MT产生的嵌合重叠群要少得多（减少50%或更多）。
