tSFM 1.0: tRNA Structure-Function Mapper.
basic_science · Level V
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- Record sourced from PubMed, PMID 33904572.
- Also identified by DOI 10.1093/bioinformatics/btab247 and PMC identifier 8545343.
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Abstract
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. 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. The data underlying this article are available on GitHub at https://github.com/tlawrence3/tSFM. Supplementary data are available at Bioinformatics online.