Apostolides Michael, Jiang Yue, Husić Mia, Siddaway Robert, Hawkins Cynthia, Turinsky Andrei L, Brudno Michael, Ramani Arun K
Centre for Computational Medicine, The Hospital For Sick Children, Toronto, ON, Canada.
The Arthur and Sonia Labatt Brain Tumour Research Centre, The Hospital for Sick Children, Toronto, ON, Canada.
Bioinformatics. 2021 Oct 11;37(19):3144-3151. doi: 10.1093/bioinformatics/btab249.
Current fusion detection tools use diverse calling approaches and provide varying results, making selection of the appropriate tool challenging. Ensemble fusion calling techniques appear promising; however, current options have limited accessibility and function.
MetaFusion is a flexible metacalling tool that amalgamates outputs from any number of fusion callers. Individual caller results are standardized by conversion into the new file type Common Fusion Format. Calls are annotated, merged using graph clustering, filtered and ranked to provide a final output of high-confidence candidates. MetaFusion consistently achieves higher precision and recall than individual callers on real and simulated datasets, and reaches up to 100% precision, indicating that ensemble calling is imperative for high-confidence results. MetaFusion uses FusionAnnotator to annotate calls with information from cancer fusion databases and is provided with a Benchmarking Toolkit to calibrate new callers.
MetaFusion is freely available at https://github.com/ccmbioinfo/MetaFusion.
Supplementary data are available at Bioinformatics online.
当前的融合检测工具采用多种调用方法，结果各异，这使得选择合适的工具颇具挑战性。集成融合调用技术似乎很有前景；然而，目前的选项在可访问性和功能方面都很有限。
MetaFusion是一种灵活的元调用工具，它能整合任意数量的融合调用器的输出。通过转换为新的文件类型通用融合格式，对各个调用器的结果进行标准化。对调用进行注释，使用图聚类进行合并、过滤和排序，以提供高置信度候选结果的最终输出。在真实和模拟数据集上，MetaFusion始终比单个调用器实现更高的精度和召回率，并且精度高达100%，这表明集成调用对于获得高置信度结果至关重要。MetaFusion使用FusionAnnotator根据癌症融合数据库中的信息对调用进行注释，并配备了一个基准测试工具包来校准新的调用器。
MetaFusion可在https://github.com/ccmbioinfo/MetaFusion上免费获取。
补充数据可在《生物信息学》在线版获取。
