FaNDOM: Fast nested distance-based seeding of optical maps.
FaNDOM: Fast nested distance-based seeding of optical maps.
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DOI：
10.1016/j.patter.2021.100248
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发表时间：
2021-05-14
期刊：
影响因子：
--
通讯作者：
Bafna V
中科院分区：
文献类型：
--
作者：
Raeisi Dehkordi S;Luebeck J;Bafna V
光学测绘(OM)提供了DNA长片段上荧光标记的序列基序的单分子读数，并解析到核苷酸水平的坐标。随着用于DNA分子分析的微流控技术的出现，以低成本产生高覆盖率的长OM数据(KBP)是可能的。除了为重新组装提供支架外，OM数据还可以与参考基因组进行比对，以识别基因组结构变体。我们引入了FANDOM(光学地图的快速嵌套距离播种)-这是一种光学地图对齐工具，它大大减少了对齐过程的搜索空间。在四个基准人类数据集上，FANDOM显著(4-14倍)快于竞争工具，同时保持了类似的敏感度和特异度。我们使用FANDOM定位了三个癌细胞系中的变异，并确定了许多生物学上有趣的结构变异，包括缺失、复制、基因融合和基因干扰重排。粉丝们可以在https://github.com/jluebeck/FaNDOM.上公开获得FANDOM是OM数据的快速开源比对方法，它利用一种新的过滤策略来缩小比对的搜索空间。该方法能够发现大型、复杂的基因组结构变体。FANDOM建议的结构变体包括基因融合和基因中断光学映射(OM)是一种快速成熟的策略，用于检测基因组中的大规模重排，利用在非常高的覆盖深度(>；100×)下成像的DNA的超长片段。OM数据反映了DNA测序的正交策略，而不是利用基于图像的检测与特定DNA基序相关联的荧光标记。由此得到的数据可以与参考基因组进行比对，以发现基因组重排和核型异常。然而，现有的方法对计算要求很高，使发现变得更加困难。我们提出了一种新的方法，FANDOM，用于将OM数据与参考基因组进行比对，并额外发现结构变体。Fandom利用基于构建基于图形的种子匹配链的快速过滤算法，实现数量级的加速，同时保持高敏感度，能够更全面地搜索涉及数百KBP的复杂结构变化。光学作图数据是一种与DNA测序正交的技术，用于识别基因组结构变异(SVS)。我们提出了一种方法，FANDOM，它执行光学定位数据与参考基因组的快速比对，以识别SVS。FANDOM使用了一种新的过滤策略，极大地减少了比对过程的搜索空间，使快速发现生物学上有趣的事件成为可能。
Optical mapping (OM) provides single-molecule readouts of fluorescently labeled sequence motifs on long fragments of DNA, resolved to nucleotide-level coordinates. With the advent of microfluidic technologies for analysis of DNA molecules, it is possible to inexpensively generate long OM data ( kbp) at high coverage. In addition to scaffolding for de novo assembly, OM data can be aligned to a reference genome for identification of genomic structural variants. We introduce FaNDOM (Fast Nested Distance Seeding of Optical Maps)—an optical map alignment tool that greatly reduces the search space of the alignment process. On four benchmark human datasets, FaNDOM was significantly (4–14×) faster than competing tools while maintaining comparable sensitivity and specificity. We used FaNDOM to map variants in three cancer cell lines and identified many biologically interesting structural variants, including deletions, duplications, gene fusions and gene-disrupting rearrangements. FaNDOM is publicly available at https://github.com/jluebeck/FaNDOM. FaNDOM is a fast open-source aligner for OM data It utilizes a novel filtering strategy to reduce the search space of alignment The method enables discovery of large, complex genomic structural variants Structural variants suggested by FaNDOM include gene fusions and gene disruptions Optical mapping (OM) is a rapidly maturing strategy for detecting large-scale rearrangements in genomes, leveraging ultra-long fragments of DNA imaged at very high depth of coverage (>100×). OM data reflect an orthogonal strategy to DNA sequencing, instead utilizing image-based detection of fluorescent tags associated with specific DNA motifs. The resulting data can be aligned back to the reference genome for discovery of genomic rearrangements and karyotypic abnormalities. Existing methods, however, are computationally demanding, making discovery harder. We present a novel method, FaNDOM, for alignment of OM data to the reference genome, and the additional discovery of structural variants. FaNDOM utilizes fast filtering algorithms based on constructing graph-based chains of seed matches, achieving orders of magnitude speedup, while maintaining high sensitivity, enabling a more comprehensive search of complex structural variations involving hundreds of kbp. Optical mapping data is an orthogonal technique to DNA sequencing for the identification of genomic structural variants (SVs). We present a method, FaNDOM, which performs fast alignment of optical mapping data to the reference genome for identification of SVs. FaNDOM utilizes a novel filtering strategy, vastly reducing the search space of the alignment process, enabling rapid discovery of biologically interesting events.
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DOI：
10.1093/bioinformatics/btx317
发表时间：
2017-09-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Leung AK;Jin N;Yip KY;Chan TF
通讯作者：
Chan TF
影响因子：
12.3
作者：
Barseghyan H;Tang W;Wang RT;Almalvez M;Segura E;Bramble MS;Lipson A;Douine ED;Lee H;Délot EC;Nelson SF;Vilain E
通讯作者：
Vilain E
影响因子：
4.6
作者：
Fontanari Krause LM;Japp AS;Krause A;Mooster J;Chopra M;Müschen M;Bohlander SK
通讯作者：
Bohlander SK
影响因子：
46.9
作者：
通讯作者：
--
影响因子：
4.8
作者：
Liu, CX;Li, YH;Bu, GJ
通讯作者：
Bu, GJ