BLESS 2：精确、内存高效且快速的纠错方法。
BLESS 2: accurate, memory-efficient and fast error correction method.
作者信息
Heo Yun, Ramachandran Anand, Hwu Wen-Mei, Ma Jian, Chen Deming
机构信息
Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
出版信息
Bioinformatics. 2016 Aug 1;32(15):2369-71. doi: 10.1093/bioinformatics/btw146. Epub 2016 Mar 24.
UNLABELLED
The most important features of error correction tools for sequencing data are accuracy, memory efficiency and fast runtime. The previous version of BLESS was highly memory-efficient and accurate, but it was too slow to handle reads from large genomes. We have developed a new version of BLESS to improve runtime and accuracy while maintaining a small memory usage. The new version, called BLESS 2, has an error correction algorithm that is more accurate than BLESS, and the algorithm has been parallelized using hybrid MPI and OpenMP programming. BLESS 2 was compared with five top-performing tools, and it was found to be the fastest when it was executed on two computing nodes using MPI, with each node containing twelve cores. Also, BLESS 2 showed at least 11% higher gain while retaining the memory efficiency of the previous version for large genomes.
AVAILABILITY AND IMPLEMENTATION
Freely available at https://sourceforge.net/projects/bless-ec
CONTACT
SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
未标注
测序数据纠错工具最重要的特性是准确性、内存效率和快速运行时间。BLESS的上一版本内存效率高且准确，但处理来自大型基因组的 reads 速度太慢。我们开发了新版本的BLESS，以提高运行时间和准确性，同时保持较小的内存使用量。新版本称为BLESS 2，其纠错算法比BLESS更准确，并且该算法已使用混合MPI和OpenMP编程进行了并行化处理。将BLESS 2与五个性能最佳的工具进行了比较，发现在使用MPI在两个计算节点上执行时，每个节点包含十二个核心，它是最快的。此外，BLESS 2在保持大型基因组上一版本内存效率的同时，增益至少高出11%。
可用性和实现方式
可在https://sourceforge.net/projects/bless-ec上免费获取
联系方式
补充信息
补充数据可在《生物信息学》在线获取。
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