Analysis of the sequence-structure relationship in RNA molecules are essential to evolutionary studies but also to concrete applications such as error-correction methodologies in sequencing technologies. The prohibitive sizes of the mutational and conformational landscapes combined with the volume of data to proceed require efficient algorithms to compute sequence-structure properties. More specifically, here we aim to calculate which mutations increase the most the likelihood of a sequence to a given structure and RNA family.
In this paper, we introduce
, an efficient linear-time and space inside-outside algorithm that computes exact mutational probabilities under secondary structure and evolutionary constraints given as a multiple sequence alignment with a consensus structure. We develop a scoring scheme combining classical stacking base pair energies to novel isostericity scales, and apply our techniques to correct point-wise errors in 5s rRNA sequences. Our results suggest that
is a promising algorithm to complement existing tools in the NGS error-correction pipeline.