RNA-eXpress

RNA-eXpress identifies and annotates transcriptional features from next-generation sequencing (NGS) read alignments to enable comprehensive, annotation-independent transcriptome analysis.


Key Features:

  • Annotation independence: Operates without relying on existing gene annotations to avoid bias toward known transcripts.
  • Broad feature identification: Detects splice variants, large and small non-coding RNAs, novel transcription start sites, alternative promoters, RNA editing events, and processing of coding transcripts.
  • Input and output formats: Accepts aligned reads in BAM format and produces study-specific feature annotations in GTF format, along with comparison statistics, sequence extraction, and feature counts.
  • Computational efficiency: Optimized for rapid processing to support large-scale transcriptome analyses.
  • Extensibility: Allows integration of new feature-identification algorithms via class extension.

Scientific Applications:

  • Discovery of regulatory elements: Identification of novel promoters and transcription start sites to study gene regulation.
  • Alternative splicing analysis: Characterization of splice variants and splicing mechanisms.
  • Non-coding RNA studies: Detection and annotation of large and small non-coding RNAs to investigate their functions.
  • RNA editing and processing research: Detection of RNA editing events and processing of coding transcripts to explore post-transcriptional modifications.

Methodology:

Processes NGS read alignments in BAM format without requiring pre-existing annotations to identify transcriptional and genomic features and outputs annotations in GTF plus comparison statistics, sequence extraction, and feature counts.

Topics

Details

Tool Type:
desktop application
Operating Systems:
Linux, Windows, Mac
Programming Languages:
Java
Added:
8/3/2017
Last Updated:
11/25/2024

Operations

Publications

Forster SC, Finkel AM, Gould JA, Hertzog PJ. RNA-eXpress annotates novel transcript features in RNA-seq data. Bioinformatics. 2013;29(6):810-812. doi:10.1093/bioinformatics/btt034. PMID:23396121. PMCID:PMC3597146.

Documentation

Links