McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Department of Biochemistry and Molecular Biology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA.
Cell Rep Methods. 2021 Oct 1;1(6):100088. doi: 10.1016/j.crmeth.2021.100088. eCollection 2021 Oct 25.
Molecular interactions at identical transcriptomic locations or at proximal but non-overlapping sites can mediate RNA modification and regulation, necessitating tools to uncover these spatial relationships. We present nearBynding, a flexible algorithm and software pipeline that models spatial correlation between transcriptome-wide tracks from diverse data types. nearBynding can process and correlate interval as well as continuous data and incorporate experimentally derived or predicted transcriptomic tracks. nearBynding offers visualization functions for its statistics to identify colocalizations and adjacent features. We demonstrate the application of nearBynding to correlate RNA-binding protein (RBP) binding preferences with other RBPs, RNA structure, or RNA modification. By cross-correlating RBP binding and RNA structure data, we demonstrate that nearBynding recapitulates known RBP binding to structural motifs and provides biological insights into RBP binding preference of G-quadruplexes. nearBynding is available as an R/Bioconductor package and can run on a personal computer, making correlation of transcriptomic features broadly accessible.
在相同转录组位置或在近端但不重叠的位置的分子相互作用可以介导 RNA 修饰和调控，这就需要有工具来揭示这些空间关系。我们提出了 nearBynding，这是一种灵活的算法和软件管道，可以对来自不同数据类型的全转录组轨迹之间的空间相关性进行建模。nearBynding 可以处理和关联区间以及连续数据，并整合实验衍生或预测的转录组轨迹。nearBynding 提供了用于识别共定位和相邻特征的统计信息的可视化功能。我们展示了 nearBynding 在将 RNA 结合蛋白 (RBP) 结合偏好与其他 RBP、RNA 结构或 RNA 修饰相关联中的应用。通过交叉相关 RBP 结合和 RNA 结构数据，我们证明 nearBynding 再现了已知的 RBP 结合到结构基序，并为 RBP 结合 G-四联体的偏好提供了生物学见解。nearBynding 作为一个 R/Bioconductor 包提供，可以在个人计算机上运行，使转录组特征的相关性广泛可用。
