MOSAIK: a hash-based algorithm for accurate next-generation sequencing short-read mapping.

MOSAIK: a hash-based algorithm for accurate next-generation sequencing short-read mapping.
复制标题

DOI:
10.1371/journal.pone.0090581
复制
发表时间:
2014
期刊:
影响因子:
3.7
通讯作者:
Marth GT
Marth GT
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Lee WP;Stromberg MP;Ward A;Stewart C;Garrison EP;Marth GT

文献摘要

参考文献

被引文献

相似文献

Mosaik是一个稳定、灵敏和开源的程序,用于将第二代和第三代测序读数映射到参考基因组。在目前的测绘工具中独一无二的是,Mosaik可以比对所有主要测序技术产生的读数,包括Illumina、应用生物系统Solid、罗氏454、离子洪流和太平洋生物科学SMRT。事实上,Mosaik是唯一为1000基因组计划中所有生成的数据(测序技术、低覆盖率和外显子组)提供一致映射的比对工具。为了提供高精度的比对,Mosaik使用了与Smith-Waterman算法相结合的哈希聚类策略。此方法非常适合捕获不匹配以及简短的插入和删除。为了支持对更大结构变体(SV)发现日益增长的兴趣,Mosaik提供了对处理已知序列SVS的显式支持,例如移动元素插入(MEI)以及生成为帮助SV发现而定制的输出。所有变体发现都得益于对读取位置置信度的准确描述。为此,Mosaik使用基于神经网络的训练方案来提供校准良好的测绘质量分数,Mosaik分配的测绘质量与实际测绘质量之间的相关系数大于0.98证明了这一点。为了确保任何基因组的研究都得到支持,提供了一条训练管道,以确保所调查基因组的最佳绘图质量分数。Mosaik是多线程的、开源的,并集成到我们的命令和管道启动器系统GKNO(http://gkno.me).
MOSAIK is a stable, sensitive and open-source program for mapping second and third-generation sequencing reads to a reference genome. Uniquely among current mapping tools, MOSAIK can align reads generated by all the major sequencing technologies, including Illumina, Applied Biosystems SOLiD, Roche 454, Ion Torrent and Pacific BioSciences SMRT. Indeed, MOSAIK was the only aligner to provide consistent mappings for all the generated data (sequencing technologies, low-coverage and exome) in the 1000 Genomes Project. To provide highly accurate alignments, MOSAIK employs a hash clustering strategy coupled with the Smith-Waterman algorithm. This method is well-suited to capture mismatches as well as short insertions and deletions. To support the growing interest in larger structural variant (SV) discovery, MOSAIK provides explicit support for handling known-sequence SVs, e.g. mobile element insertions (MEIs) as well as generating outputs tailored to aid in SV discovery. All variant discovery benefits from an accurate description of the read placement confidence. To this end, MOSAIK uses a neural-network based training scheme to provide well-calibrated mapping quality scores, demonstrated by a correlation coefficient between MOSAIK assigned and actual mapping qualities greater than 0.98. In order to ensure that studies of any genome are supported, a training pipeline is provided to ensure optimal mapping quality scores for the genome under investigation. MOSAIK is multi-threaded, open source, and incorporated into our command and pipeline launcher system GKNO (http://gkno.me).
DOI: 10.1038/ng.437
发表时间: 2009-10
期刊: NATURE GENETICS
影响因子: 30.8
作者:
Alkan, Can;Kidd, Jeffrey M.;Marques-Bonet, Tomas;Aksay, Gozde;Antonacci, Francesca;Hormozdiari, Fereydoun;Kitzman, Jacob O.;Baker, Carl;Malig, Maika;Mutlu, Onur;Sahinalp, S. Cenk;Gibbs, Richard A.;Eichler, Evan E.
通讯作者: Eichler, Evan E.
DOI: 10.1093/bioinformatics/bts712
发表时间: 2013-02-01
期刊: BIOINFORMATICS
影响因子: 5.8
作者:
Gontarz, Paul M.;Berger, Jennifer;Wong, Chung F.
通讯作者: Wong, Chung F.
DOI: 10.1371/journal.pone.0005972
发表时间: 2009-06-22
期刊: PloS one
影响因子: 3.7
作者:
Costantini M;Bernardi G
通讯作者: Bernardi G
DOI: 10.1145/1082036.1082039
发表时间: 2005-07-01
期刊: JOURNAL OF THE ACM
影响因子: 2.5
作者:
Ferragina, P;Manzini, G
通讯作者: Manzini, G
DOI: 10.1016/j.vaccine.2011.04.131
发表时间: 2011-07-12
期刊: VACCINE
影响因子: 5.5
作者:
Dark, Michael J.;Al-Khedery, Basima;Barbet, Anthony F.
通讯作者: Barbet, Anthony F.