Group of Computational Neurogenomics, D-HEST Institute for Neurosciences, ETH Zürich, Winterthurerstrasse 190, 8057, Zurich, Switzerland.
Lab of Systems Neuroscience, D-HEST Institute for Neurosciences, ETH Zürich, Winterthurerstrasse 190, 8057, Zurich, Switzerland.
BMC Bioinformatics. 2021 Apr 13;22(1):189. doi: 10.1186/s12859-021-04114-7.
Despite the importance of alternative poly-adenylation and 3' UTR length for a variety of biological phenomena, there are limited means of detecting UTR changes from standard transcriptomic data.
We present the diffUTR Bioconductor package which streamlines and improves upon differential exon usage (DEU) analyses, and leverages existing DEU tools and alternative poly-adenylation site databases to enable differential 3' UTR usage analysis. We demonstrate the diffUTR features and show that it is more flexible and more accurate than state-of-the-art alternatives, both in simulations and in real data.
diffUTR enables differential 3' UTR analysis and more generally facilitates DEU and the exploration of their results.
尽管可变聚腺苷酸化和 3'UTR 长度对各种生物学现象都很重要，但从标准转录组数据中检测 UTR 变化的方法有限。
我们提出了 diffUTR Bioconductor 包，它简化并改进了差异外显子使用（DEU）分析，并利用现有的 DEU 工具和可变多聚腺苷酸化位点数据库来实现差异 3'UTR 使用分析。我们展示了 diffUTR 的特点，并表明它在模拟和真实数据中比最先进的替代方法更灵活、更准确。
diffUTR 能够进行差异 3'UTR 分析，更一般地促进了 DEU 及其结果的探索。
