MINES

MINES (Modification Identification using Nanopore Sequencing) is a software tool that identifies RNA modifications using direct RNA sequencing data from Oxford Nanopore Technologies (ONT). The tool employs machine learning, specifically a random forest classifier, to detect modified bases at single-coordinate resolution.

Key features of MINES:

1. Utilizes raw sequencing output from ONT's direct RNA sequencing technology.

2. Trained using experimentally detected RNA modifications to improve accuracy.

3. Enables de novo identification of RNA modifications without prior knowledge of their positions.

4. Provides single-coordinate resolution, allowing for precise mapping of modified bases.

5. Addresses the challenge of interpreting raw sequencing data to discover modified bases.

Topic

Gene transcripts;RNA-Seq;Gene expression;Functional, regulatory and non-coding RNA;Sequence sites, features and motifs

Detail

  • Operation: Post-translation modification site prediction;Sequence motif recognition;de Novo sequencing

  • Software interface: Command-line user interface

  • Language: Python

  • License: Not stated

  • Cost: Free of charge

  • Version name: -

  • Credit: The National Institutes of Health.

  • Input: -

  • Output: -

  • Contact: Gene W. Yeo geneyeo@ucsd.edu

  • Collection: -

  • Maturity: -

Publications

  • Direct RNA sequencing enables m<sup>6</sup>A detection in endogenous transcript isoforms at base-specific resolution.
  • Lorenz DA, et al. Direct RNA sequencing enables m<sup>6</sup>A detection in endogenous transcript isoforms at base-specific resolution. Direct RNA sequencing enables m<sup>6</sup>A detection in endogenous transcript isoforms at base-specific resolution. 2020; 26:19-28. doi: 10.1261/rna.072785.119
  • https://doi.org/10.1261/RNA.072785.119
  • PMID: 31624092
  • PMC: PMC6913132

Download and documentation

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