Department of Urology and Department of Bioinformatics, Erasmus University Medical Center, Rotterdam, 3000 CA, The Netherlands.
Department of Urology and.
Bioinformatics. 2016 Apr 15;32(8):1226-8. doi: 10.1093/bioinformatics/btv721. Epub 2015 Dec 10.
A new generation of tools that identify fusion genes in RNA-seq data is limited in either sensitivity and or specificity. To allow further downstream analysis and to estimate performance, predicted fusion genes from different tools have to be compared. However, the transcriptomic context complicates genomic location-based matching. FusionMatcher (FuMa) is a program that reports identical fusion genes based on gene-name annotations. FuMa automatically compares and summarizes all combinations of two or more datasets in a single run, without additional programming necessary. FuMa uses one gene annotation, avoiding mismatches caused by tool-specific gene annotations. FuMa matches 10% more fusion genes compared with exact gene matching due to overlapping genes and accepts intermediate output files that allow a stepwise analysis of corresponding tools.
The code is available at: https://github.com/ErasmusMC-Bioinformatics/fuma and available for Galaxy in the tool sheds and directly accessible at https://bioinf-galaxian.erasmusmc.nl/galaxy/
y.hoogstrate@erasmusmc.nl or a.stubbs@erasmusmc.nl
Supplementary data are available at Bioinformatics online.
新一代的 RNA-seq 数据融合基因识别工具在灵敏度和/或特异性方面存在局限性。为了进行进一步的下游分析和评估性能，必须比较来自不同工具的预测融合基因。然而，转录组背景使得基于基因组位置的匹配变得复杂。FusionMatcher（FuMa）是一个基于基因名称注释报告相同融合基因的程序。FuMa 可以在单个运行中自动比较和总结两个或更多数据集的所有组合，而无需额外的编程。FuMa 使用一个基因注释，避免了由于工具特定的基因注释而导致的不匹配。由于重叠基因，FuMa 比精确的基因匹配多匹配 10%的融合基因，并接受中间输出文件，允许对相应工具进行逐步分析。
该代码可在以下网址获得：https://github.com/ErasmusMC-Bioinformatics/fuma，并可在 Galaxy 的工具库中获得，也可直接在 https://bioinf-galaxian.erasmusmc.nl/galaxy/ 访问。
y.hoogstrate@erasmusmc.nl 或 a.stubbs@erasmusmc.nl
补充数据可在 Bioinformatics 在线获得。
