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.

SUBMITTER: Lawrence TJ 

PROVIDER: S-EPMC8545343 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature