Department of Biomedical informatics, Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan.
Bioinformatics. 2013 Apr 15;29(8):1004-10. doi: 10.1093/bioinformatics/btt092. Epub 2013 Mar 1.
High-accuracy de novo assembly of the short sequencing reads from RNA-Seq technology is very challenging. We introduce a de novo assembly algorithm, EBARDenovo, which stands for Extension, Bridging And Repeat-sensing Denovo. This algorithm uses an efficient chimera-detection function to abrogate the effect of aberrant chimeric reads in RNA-Seq data.
EBARDenovo resolves the complications of RNA-Seq assembly arising from sequencing errors, repetitive sequences and aberrant chimeric amplicons. In a series of assembly experiments, our algorithm is the most accurate among the examined programs, including de Bruijn graph assemblers, Trinity and Oases.
EBARDenovo is available at http://ebardenovo.sourceforge.net/. This software package (with patent pending) is free of charge for academic use only.
Supplementary data are available at Bioinformatics online.
从 RNA-Seq 技术的短测序读长进行高精度从头组装非常具有挑战性。我们引入了一种从头组装算法，EBARDenovo，它代表扩展、桥接和重复感应从头组装。该算法使用高效的嵌合体检测功能消除 RNA-Seq 数据中异常嵌合体读的影响。
EBARDenovo 解决了由于测序错误、重复序列和异常嵌合扩增子而导致的 RNA-Seq 组装的复杂性。在一系列组装实验中，我们的算法在被检查的程序中是最准确的，包括 de Bruijn 图组装器、Trinity 和 Oases。
EBARDenovo 可在 http://ebardenovo.sourceforge.net/ 获得。该软件包（正在申请专利）仅供学术用途免费使用。
补充数据可在生物信息学在线获得。
