Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan.
PLoS One. 2013;8(3):e60843. doi: 10.1371/journal.pone.0060843. Epub 2013 Mar 28.
A plethora of algorithmic assemblers have been proposed for the de novo assembly of genomes, however, no individual assembler guarantees the optimal assembly for diverse species. Optimizing various parameters in an assembler is often performed in order to generate the most optimal assembly. However, few efforts have been pursued to take advantage of multiple assemblies to yield an assembly of high accuracy. In this study, we employ various state-of-the-art assemblers to generate different sets of contigs for bacterial genomes. A tool, named CISA, has been developed to integrate the assemblies into a hybrid set of contigs, resulting in assemblies of superior contiguity and accuracy, compared with the assemblies generated by the state-of-the-art assemblers and the hybrid assemblies merged by existing tools. This tool is implemented in Python and requires MUMmer and BLAST+ to be installed on the local machine. The source code of CISA and examples of its use are available at http://sb.nhri.org.tw/CISA/.
已经提出了许多算法组装器来进行基因组从头组装，然而，没有任何一个组装器能保证为不同的物种生成最佳的组装。为了生成最佳的组装，通常需要优化组装器中的各种参数。然而，很少有研究利用多个组装来生成高精度的组装。在本研究中，我们使用各种最先进的组装器为细菌基因组生成不同的 contigs 集。开发了一个名为 CISA 的工具，用于将组装集成到一个混合的 contigs 集中，与最先进的组装器生成的组装以及现有工具合并的混合组装相比，该混合 contigs 集具有更好的连续性和准确性。该工具是用 Python 编写的，需要在本地机器上安装 MUMmer 和 BLAST+。CISA 的源代码及其使用示例可在 http://sb.nhri.org.tw/CISA/ 上获得。
