BBMerge - Accurate paired shotgun read merging via overlap.
BBMerge - Accurate paired shotgun read merging via overlap.
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DOI：
10.1371/journal.pone.0185056
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发表时间：
2017
期刊：
影响因子：
3.7
通讯作者：
Singer E
中科院分区：
文献类型：
--
作者：
Bushnell B;Rood J;Singer E
合并在高通量测序平台上生成的双端鸟枪读段可以显著改善各种后续生物信息学过程，包括基因组组装、分箱、作图、注释和聚类以用于分类学分析。随着序列数据量和CPU核心数量的不可阻挡的增长，读取处理工具的速度和可扩展性变得越来越重要。鸟枪式读数合并的准确性也是至关重要的，因为不正确的合并引入的错误会渗透到下游分析的质量中。因此，我们设计了一种新的工具，以最大限度地提高准确性并最大限度地减少处理时间，允许在较大的数据集上使用读取合并，并在对错误高度敏感的分析中使用。我们提出了BBMerge，一个新的双端鸟枪序列数据的合并工具。我们通过与其他八种广泛使用的合并工具进行比较来对BBMerge进行基准测试，评估速度，准确性和可扩展性。对合成和真实世界数据集的评估表明，BBMerge产生的合并鸟枪读数比任何现有的合并工具都更准确，速度更快。BBMerge还提供了通过使用k-mer频率信息来组装读段之间的未测序间隙来合并非重叠鸟枪读段对的能力，从而在保持或提高准确性的同时实现显著更高的合并率。
Merging paired-end shotgun reads generated on high-throughput sequencing platforms can substantially improve various subsequent bioinformatics processes, including genome assembly, binning, mapping, annotation, and clustering for taxonomic analysis. With the inexorable growth of sequence data volume and CPU core counts, the speed and scalability of read-processing tools becomes ever-more important. The accuracy of shotgun read merging is crucial as well, as errors introduced by incorrect merging percolate through to reduce the quality of downstream analysis. Thus, we designed a new tool to maximize accuracy and minimize processing time, allowing the use of read merging on larger datasets, and in analyses highly sensitive to errors. We present BBMerge, a new merging tool for paired-end shotgun sequence data. We benchmark BBMerge by comparison with eight other widely used merging tools, assessing speed, accuracy and scalability. Evaluations of both synthetic and real-world datasets demonstrate that BBMerge produces merged shotgun reads with greater accuracy and at higher speed than any existing merging tool examined. BBMerge also provides the ability to merge non-overlapping shotgun read pairs by using k-mer frequency information to assemble the unsequenced gap between reads, achieving a significantly higher merge rate while maintaining or increasing accuracy.
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影响因子：
9.8
作者：
Singer E;Andreopoulos B;Bowers RM;Lee J;Deshpande S;Chiniquy J;Ciobanu D;Klenk HP;Zane M;Daum C;Clum A;Cheng JF;Copeland A;Woyke T
通讯作者：
Woyke T
影响因子：
56.9
作者：
Shendure, J;Porreca, GJ;Church, GM
通讯作者：
Church, GM
影响因子：
3.7
作者：
Holodniy, Mark;Brown, Sheldon T.;Darbyshire, Janet
通讯作者：
Darbyshire, Janet
影响因子：
14.9
作者：
Renaud G;Stenzel U;Kelso J
通讯作者：
Kelso J
DOI：
10.1093/bioinformatics/btt593
发表时间：
2014-03-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Zhang J;Kobert K;Flouri T;Stamatakis A
通讯作者：
Stamatakis A