tSFM 1.0: tRNA Structure-Function Mapper.

MOTIVATION Structure-conditioned information statistics have proven useful to predict and visualize tRNA Class-Informative Features (CIFs) and their evolutionary divergences. Although permutation p-values can quantify the significance of CIF divergences between two taxa, their naive Monte Carlo approximation is slow and inaccurate. The Peaks-over-Threshold approach of Knijnenburg et al. (2009) promises improvements to both speed and accuracy of permutation p-values, but has no publicly available API. AVAILABILITY AND IMPLEMENTATION We present tRNA Structure-Function Mapper (tSFM) v1.0, an open-source, multi-threaded application that efficiently computes, visualizes, and assesses significance of single- and paired-site CIFs and their evolutionary divergences for any RNA, protein, gene or genomic element sequence family. multiple estimators of permutation p-values for CIF evolutionary divergences are provided along with condidence intervals. tSFM is implemented in Python 3 with compiled C extensions and is freely available through GitHub (https://github.com/tlawrence3/tSFM) and PyPI. SUPPLEMENTARY INFORMATION Supplementary materials are available at Bioinformatics online.