tRNAstudio: facilitating the study of human mature tRNAs from deep sequencing datasets

Bioinformatics. 2022 May 13;38(10):2934-2936. doi: 10.1093/bioinformatics/btac198.

Abstract

Summary: High-throughput sequencing of transfer RNAs (tRNA-Seq) is a powerful approach to characterize the cellular tRNA pool. Currently, however, analyzing tRNA-Seq datasets requires strong bioinformatics and programming skills. tRNAstudio facilitates the analysis of tRNA-Seq datasets and extracts information on tRNA gene expression, post-transcriptional tRNA modification levels, and tRNA processing steps. Users need only running a few simple bash commands to activate a graphical user interface that allows the easy processing of tRNA-Seq datasets in local mode. Output files include extensive graphical representations and associated numerical tables, and an interactive html summary report to help interpret the data. We have validated tRNAstudio using datasets generated by different experimental methods and derived from human cell lines and tissues that present distinct patterns of tRNA expression, modification and processing.

Availability and implementation: Freely available at https://github.com/GeneTranslationLab-IRB/tRNAstudio under an open-source GNU GPL v3.0 license.

Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • High-Throughput Nucleotide Sequencing / methods
  • Humans
  • RNA Processing, Post-Transcriptional
  • RNA, Transfer* / genetics
  • Sequence Analysis, RNA / methods
  • Software*

Substances

  • RNA, Transfer