MINTIE: identifying novel structural and splice variants in transcriptomes using RNA-seq data
- Author(s)
- Cmero, M; Schmidt, B; Majewski, IJ; Ekert, PG; Oshlack, A; Davidson, NM;
- Journal Title
- Genome Biology
- Publication Type
- Research article
- Abstract
- Calling fusion genes from RNA-seq data is well established, but other transcriptional variants are difficult to detect using existing approaches. To identify all types of variants in transcriptomes we developed MINTIE, an integrated pipeline for RNA-seq data. We take a reference-free approach, combining de novo assembly of transcripts with differential expression analysis to identify up-regulated novel variants in a case sample. We compare MINTIE with eight other approaches, detecting > 85% of variants while no other method is able to achieve this. We posit that MINTIE will be able to identify new disease variants across a range of disease types.
- Keywords
- Algorithms; Genetic Variation; Humans; Precursor B-Cell Lymphoblastic Leukemia-Lymphoma/genetics; *RNA Splicing; *RNA-Seq; Rare Diseases/genetics; *Software; *Transcriptome
- Department(s)
- Laboratory Research
- PubMed ID
- 34686194
- Publisher's Version
- https://doi.org/10.1186/s13059-021-02507-8
- Open Access at Publisher's Site
https://doi.org/10.1186/s13059-021-02507-8- Terms of Use/Rights Notice
- Refer to copyright notice on published article.
Creation Date: 2025-08-29 05:47:51
Last Modified: 2025-08-29 05:53:29