Spatial Correlation Statistics Enable Transcriptome-Wide Characterization of RNA Structure Binding

Biologically important relationships can occur at identical transcriptomic locations or at proximal but non-overlapping sites, necessitating tools to uncover these spatial relationships. We present nearBynding, an algorithm that models spatial correlation between transcriptomic data types, such as RNA-binding protein (RBP) binding preferences, RNA structure and RNA modification. nearBynding can visualize overlapping colocalizations and adjacent features, analyze minimally processed (e.g. non-peak-called) data, and incorporate diverse, experimentally-derived or in silico predicted transcriptomic data types. By cross-correlating RBP binding and RNA structure data, we demonstrate that nearBynding recapitulates known RBP binding to structural motifs and provides novel 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 transcriptome-wide correlation of RNA features broadly accessible.