Work

PSQAN: a pipeline to prioritize novel and biologically relevant transcripts from long-read RNA sequencing

Year: 2024

Type: article

Abstract: Motivation: Long-read RNA sequencing has the potential to accurately quantify transcriptomes and reveal the isoform diversity of disease-causing genes. However, despite the recent advances in analysis tools for transcript discovery, long-read RNA sequencing data is still challenging to analyse, due to the detection of hundreds or even thousands of novel transcripts per gene. Results: Here, we introduce PSQAN, a workflow to help researchers prioritize high-confidence and potentially biologically relevant transcripts associated with candidate genes and make transcript characterization results more interpretable. PSQAN performs a gene-based analysis on characterized transcripts generated by SQANTI3 and TALON. PSQAN re-groups transcripts into easily interpretable categories to facilitate their prioritization, allows transcript-level expression thresholds, and generates visualizations to determine optimal expression thresholds. Overall, we demonstrate that PSQAN is a useful tool which enables users to identify known and novel transcripts of potential biological importance. Availability and implementation: PSQAN is an analysis workflow implemented in Snakemake and R and is licensed under the GNU General Public License version 3. The source code and documentation of this tool is available at https://github.com/sid-sethi/PSQAN.

Source: Bioinformatics Advances

DOI: 10.1093/bioadv/vbaf293

Authors: Siddharth Sethi, Emil K Gustavsson, Harpreet Saini, Mina Ryten

Institutions: Astex Pharmaceuticals, University College London, University of Cambridge

Language: English

Topic: Genomics and Phylogenetic Studies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $2,917

Funders: BrightFocus Foundation, Astex Pharmaceuticals