tSFM 1.0: tRNA Structure-Function Mapper.

ABSTRACT

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. RESULTS: 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 confidence intervals. tSFM is implemented in Python 3 with compiled C extensions and is freely available through GitHub (https//github.com/tlawrence3/tSFM) and PyPI. AVAILABILITY AND IMPLEMENTATION The data underlying this article are available on GitHub at https//github.com/tlawrence3/tSFM. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.