Sequence census methods reduce molecular measurements such as transcript 
abundance and protein-nucleic acid interactions to counting problems via DNA 
sequencing. We focus on a novel assay utilizing this approach, called selective 
2'-hydroxyl acylation analyzed by primer extension sequencing (SHAPE-Seq), that 
can be used to characterize RNA secondary and tertiary structure. We describe a 
fully automated data analysis pipeline for SHAPE-Seq analysis that includes read 
processing, mapping, and structural inference based on a model of the 
experiment. Our methods rely on the solution of a series of convex optimization 
problems for which we develop efficient and effective numerical algorithms. Our 
results can be easily extended to other chemical probes of RNA structure, and 
also generalized to modeling polymerase drop-off in other sequence census-based 
experiments.