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;
- Details
- Publication Year 2021-10-22,Volume 22,Issue #1,Page 296
- Journal Title
- Genome Biology
- 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.
- Publisher
- BMC
- Research Division(s)
- Blood Cells And Blood Cancer
- 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- NHMRC Grants
- NHMRC/1140626,
- Terms of Use/Rights Notice
- Refer to copyright notice on published article.
Creation Date: 2021-11-09 10:48:04
Last Modified: 2021-12-07 09:23:14