SQANTI-SIM: a simulator of controlled transcript novelty for lrRNA-seq benchmark

Genome Biol. 2023 Dec 11;24(1):286. doi: 10.1186/s13059-023-03127-0.

Abstract

Long-read RNA sequencing has emerged as a powerful tool for transcript discovery, even in well-annotated organisms. However, assessing the accuracy of different methods in identifying annotated and novel transcripts remains a challenge. Here, we present SQANTI-SIM, a versatile tool that wraps around popular long-read simulators to allow precise management of transcript novelty based on the structural categories defined by SQANTI3. By selectively excluding specific transcripts from the reference dataset, SQANTI-SIM effectively emulates scenarios involving unannotated transcripts. Furthermore, the tool provides customizable features and supports the simulation of additional types of data, representing the first multi-omics simulation tool for the lrRNA-seq field.

Keywords: Isoform discovery; Long-read transcriptomics; SQANTI; Transcript simulation; Transcriptome reconstruction.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, N.I.H., Extramural

MeSH terms

  • Base Sequence
  • Benchmarking*
  • Computer Simulation
  • Gene Expression Profiling
  • High-Throughput Nucleotide Sequencing
  • Sequence Analysis, RNA
  • Transcriptome*