  In a recent paper Siegfried et al. published a new sequence-based structural
RNA assay that utilizes mutational profiling to detect base pairing (MaP).
Output from MaP provides information about both pairing (via reactivities) and
contact (via correlations). Reactivities can be coupled to partition function
folding models for structural inference, while correlations can reveal pairs of
sites that may be in structural proximity. The possibility for inference of 3D
contacts via MaP suggests a novel approach to structural prediction for RNA
analogous to covariance structural prediction for proteins. We explore this
approach and show that partial correlation analysis outperforms na\"ive
correlation analysis. Our results should be applicable to a wide range of
high-throughput sequencing based RNA structural assays that are under
development.
