Program in Computational Biology and Bioinformatics, Yale University, 300 George Street, New Haven, CT 06511, USA.
Genome Biol. 2010;11(10):R104. doi: 10.1186/gb-2010-11-10-r104. Epub 2010 Oct 21.
We have developed FusionSeq to identify fusion transcripts from paired-end RNA-sequencing. FusionSeq includes filters to remove spurious candidate fusions with artifacts, such as misalignment or random pairing of transcript fragments, and it ranks candidates according to several statistics. It also has a module to identify exact sequences at breakpoint junctions. FusionSeq detected known and novel fusions in a specially sequenced calibration data set, including eight cancers with and without known rearrangements.
我们开发了 FusionSeq 来从配对的 RNA 测序数据中识别融合转录本。FusionSeq 包括过滤器，用于去除具有伪影的假阳性候选融合，例如转录本片段的错配或随机配对，并且它根据几个统计数据对候选进行排序。它还有一个模块用于识别断点连接处的精确序列。FusionSeq 在专门测序的校准数据集（包括 8 种具有和不具有已知重排的癌症）中检测到了已知和新的融合。
