FusionMap: detecting fusion genes from next-generation sequencing data at base-pair resolution
FusionMap: detecting fusion genes from next-generation sequencing data at base-pair resolution
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DOI：
10.1093/bioinformatics/btr310
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发表时间：
2011-07-15
期刊：
影响因子：
5.8
通讯作者：
Hoeck, Wolfgang
中科院分区：
文献类型：
--
作者：
Ge, Huanying;Liu, Kejun;Hoeck, Wolfgang
动机：下一代测序技术产生高通量数据，这使我们能够在转录和基因组水平上检测融合基因。为了检测融合基因，目前的生物信息学工具严重依赖于双端方法，而忽略了跨越融合连接的读数的重要性。因此，有必要开发一种有效的对准检测融合事件的准确映射这些交界处跨越单reads，特别是当读得到更长的改进测序technology.Results：我们提出了一种新的方法，FusionMap，它对准融合读取直接到基因组，而无需事先了解潜在的融合区域。FusionMap可以检测来自RNA-Seq或gDNA-Seq研究的单端和双端数据集中的融合事件，并以碱基对分辨率表征融合连接。我们发现，FusionMap在两个模拟RNA-Seq数据集上的融合检测中具有高灵敏度和特异性，其中包含75 nt配对末端读段。当读取对之间的内部距离较小时，FusionMap实现了比配对末端方法高得多的灵敏度和特异性。利用FusionMap对K562慢性粒细胞白血病细胞系中的融合基因进行表征，我们进一步证明了其在单端RNA-Seq和gDNA-Seq数据集中融合检测的准确性。这些组合结果表明，FusionMap提供了一个准确和系统的解决方案，通过跨连接读取检测融合事件。
Motivation: Next generation sequencing technology generates high-throughput data, which allows us to detect fusion genes at both transcript and genomic levels. To detect fusion genes, the current bioinformatics tools heavily rely on paired-end approaches and overlook the importance of reads that span fusion junctions. Thus there is a need to develop an efficient aligner to detect fusion events by accurate mapping of these junction-spanning single reads, particularly when the read gets longer with the improvement in sequencing technology.Results: We present a novel method, FusionMap, which aligns fusion reads directly to the genome without prior knowledge of potential fusion regions. FusionMap can detect fusion events in both single- and paired-end datasets from either RNA-Seq or gDNA-Seq studies and characterize fusion junctions at base-pair resolution. We showed that FusionMap achieved high sensitivity and specificity in fusion detection on two simulated RNA-Seq datasets, which contained 75 nt paired-end reads. FusionMap achieved substantially higher sensitivity and specificity than the paired-end approach when the inner distance between read pairs was small. Using FusionMap to characterize fusion genes in K562 chronic myeloid leukemia cell line, we further demonstrated its accuracy in fusion detection in both single-end RNA-Seq and gDNA-Seq datasets. These combined results show that FusionMap provides an accurate and systematic solution to detecting fusion events through junction-spanning reads.