RNA的反向剪接导致了环状而非线性的转录本，称为环状RNA。最近发现的且尚不完全了解的一类由多个基因组成的环状RNA子集，称为融合来源的环状RNA（fusion-derived circular RNAs，fcircRNAs），代表了一类具有致癌潜力的潜在生物标志物。现有的分析工具难以检测fcircRNAs，这使得对它们的普遍性和功能进行更全面的评估变得困难。改进的检测方法可能会导致有关fcircRNAs的更多生物学和临床见解。我们开发了第一个无偏见的工具用于从RNA-Seq数据中检测fcircRNAs（INTEGRATE-Circ），并通过可视化工具（INTEGRATE-Vis）可视化fcircRNAs。通过对模拟RNA-Seq数据的分析，我们发现INTEGRATE-Circ比其他工具更敏感、精确和准确，且通过对公开的淋巴母细胞系数据的分析，我们的工具能够超越其他工具。最后，我们能够在良好表征的乳腺癌细胞系中验证INTEGRATE-Circ检测到的三个新型的fcircRNAs。INTEGRATE-Circ和INTEGRATE-Vis的开源代码可在https://www.github.com/ChrisMaherLab/INTEGRATE-CIRC和https://www.github.com/ChrisMaherLab/INTEGRATE-Vis上获取。补充数据可在Bioinformatics在线获取。© 2023年作者授权，由牛津大学出版。

Backsplicing of RNA results in circularized rather than linear transcripts, known as circular RNA. A recently discovered and poorly understood subset of circular RNAs that are composed of multiple genes, termed fusion-derived circular RNAs (fcircRNAs), represent a class of potential biomarkers shown to have oncogenic potential. Detection of fcircRNAs eludes existing analytical tools, making it difficult to more comprehensively assess their prevalence and function. Improved detection methods may lead to additional biological and clinical insights related to fcircRNAs.We developed the first unbiased tool for detecting fcircRNAs (INTEGRATE-Circ) and visualizing fcircRNAs (INTEGRATE-Vis) from RNA-Seq data. We found that INTEGRATE-Circ was more sensitive, precise and accurate than other tools based on our analysis of simulated RNA-Seq data and our tool was able to outperform other tools in an analysis of public lymphoblast cell line data. Finally, we were able to validate in vitro three novel fcircRNAs detected by INTEGRATE-Circ in a well characterized breast cancer cell line.Open source code for INTEGRATE-Circ and INTEGRATE-Vis is available at https://www.github.com/ChrisMaherLab/INTEGRATE-CIRC and https://www.github.com/ChrisMaherLab/INTEGRATE-Vis.Supplementary data are available at Bioinformatics online.© The Author(s) 2023. Published by Oxford University Press.