@article {Li063107, author = {Bo Li and Akshay Tambe and Sharon Aviran and Lior Pachter}, title = {Prober: A general toolkit for analyzing sequencing-based {\textquoteleft}toeprinting{\textquoteright} assays}, elocation-id = {063107}, year = {2016}, doi = {10.1101/063107}, publisher = {Cold Spring Harbor Laboratory}, abstract = {A number of high-throughput transcriptase drop-off assays have recently been developed to probe post-transcriptional dynamics of RNA-protein interaction, RNA structure, and post-transcriptional modifications. Although these assays survey a diverse set of {\textquoteleft}epitranscriptomic{\textquoteright} marks, they share methodological similarities and as such their interpretation is predicated on addressing similar computational challenges. Among these, a key question is how to learn isoform-specific chemical modification profiles in the face of complex read multi-mapping. In this paper, we propose PROBer, the first rigorous statistical model to handle these challenges for a general set of sequencing-based {\textquoteleft}toeprinting{\textquoteright} assays.}, URL = {https://www.biorxiv.org/content/early/2016/07/12/063107}, eprint = {https://www.biorxiv.org/content/early/2016/07/12/063107.full.pdf}, journal = {bioRxiv} }