SatuRn: Scalable analysis of differential transcript usage for bulk and single-cell RNA-sequencing applications
Research output: Contribution to journal › Journal article › Research › peer-review
Documents
- Fulltext
Final published version, 5.18 MB, PDF document
Alternative splicing produces multiple functional transcripts from a single gene. Dysregulation of splicing is known to be associated with disease and as a hallmark of cancer. Existing tools for differential transcript usage (DTU) analysis either lack in performance, cannot account for complex experimental designs or do not scale to massive single-cell transcriptome sequencing (scRNA-seq) datasets. We introduce satuRn, a fast and flexible quasi-binomial generalized linear modelling framework that is on par with the best performing DTU methods from the bulk RNA-seq realm, while providing good false discovery rate control, addressing complex experimental designs, and scaling to scRNA-seq applications.
Original language | English |
---|---|
Article number | 374 |
Journal | F1000Research |
Volume | 10 |
Number of pages | 43 |
ISSN | 2046-1402 |
DOIs | |
Publication status | Published - 2022 |
Bibliographical note
Publisher Copyright:
© 2022 Gilis J et al.
- Differential transcript usage, RNA-seq, SatuRn, Single-cell transcriptomics, Splicing, Statistical framework
Research areas
ID: 343299032