Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna, Medical University of Vienna, Dr. Bohrgasse 9, A-1030 Vienna, Austria and Bioinformatics and Computational Biology, Faculty of Computer Science, University of Vienna, Waehringerstrasse 17, A-1090 Vienna, Austria.
Bioinformatics. 2013 Nov 1;29(21):2790-1. doi: 10.1093/bioinformatics/btt468. Epub 2013 Aug 23.
When choosing a read mapper, one faces the trade off between speed and the ability to map reads in highly polymorphic regions. Here, we report NextGenMap, a fast and accurate read mapper, which reduces this dilemma. NextGenMap aligns reads reliably to a reference genome even when the sequence difference between target and reference genome is large, i.e. highly polymorphic genome. At the same time, NextGenMap outperforms current mapping methods with respect to runtime and to the number of correctly mapped reads. NextGenMap efficiently uses the available hardware by exploiting multi-core CPUs as well as graphic cards (GPUs), if available. In addition, NextGenMap handles automatically any read data independent of read length and sequencing technology.
NextGenMap source code and documentation are available at: http://cibiv.github.io/NextGenMap/.
Supplementary data are available at Bioinformatics online.
在选择读取映射器时,人们面临着速度和在高度多态区域中映射读取的能力之间的权衡。在这里,我们报告了 NextGenMap,这是一种快速而准确的读取映射器,可以减少这种困境。NextGenMap 可以可靠地将读取与参考基因组对齐,即使目标基因组与参考基因组之间的序列差异很大,即高度多态基因组。同时,NextGenMap 在运行时和正确映射的读取数量方面优于当前的映射方法。NextGenMap 通过利用多核 CPU 以及图形卡(GPU)(如果可用),有效地利用了可用的硬件。此外,NextGenMap 自动处理任何读取数据,而与读取长度和测序技术无关。
NextGenMap 的源代码和文档可在以下网址获得:http://cibiv.github.io/NextGenMap/。
补充数据可在 Bioinformatics 在线获得。