Department of Biomedical Engineering and Genome Center, University of California, Davis, One Shields Avenue, Davis, 95616, CA, USA.
Department of Biochemistry, Purdue University, BCHM 305, 175 S. University Street, West Lafayette, 47907-2063, IN, USA.
Genome Biol. 2019 Feb 21;20(1):40. doi: 10.1186/s13059-019-1641-3.
RNA biology is revolutionized by recent developments of diverse high-throughput technologies for transcriptome-wide profiling of molecular RNA structures. RNA structurome profiling data can be used to identify differentially structured regions between groups of samples. Existing methods are limited in scope to specific technologies and/or do not account for biological variation. Here, we present dStruct which is the first broadly applicable method for differential analysis accounting for biological variation in structurome profiling data. dStruct is compatible with diverse profiling technologies, is validated with experimental data and simulations, and outperforms existing methods.
RNA 生物学正在经历一场革命，这得益于高通量技术的最新发展，这些技术可以对分子 RNA 结构进行全转录组分析。RNA 结构组谱分析数据可用于识别不同样本组之间结构不同的区域。现有的方法在范围上受到特定技术的限制，或者没有考虑到生物学变化。在这里，我们提出了 dStruct，这是第一个广泛适用的方法，可以对结构组谱分析数据中的生物学变化进行差异分析。dStruct 与多种分析技术兼容，经过实验数据和模拟验证，并优于现有方法。
