- [29/05/2022] We have released v2.2 that fully supports counting droplet-based data for both Skipping Exon events and other types of splcing events. See the brie-count manual
- [29/05/2022] We have include small-sized test data sets (15MB) for both smart-seq2 and 10x Genomics. See data in brie-tutorials/tests repo
Welcome to the new BRIE (>=2.0 or BRIE2), Bayesian Regression for Isoform Estimate, a scalable Bayesian method to accurately identify splicing phenotypes in single-cell RNA-seq experiments and quantify isoform proportions and their uncertainty.
BRIE2 supports the analysis of splicing processes at two molecular levels, either between alternative splicing isoforms or between unspliced and spliced RNAs. In either case, it returns cell-by-event or cell-by-gene matrices of PSI value and its 95% confidence interval (quantification) and the statistics for detecting DAS and DMG on each event or gene:
- Differential alternative splicing (DAS): This task is to quantify the proportions of alternative splicing isoforms and to detect DAS between groups of cells or along with a continuous covariate, e.g., pseudotime. BRIE2 is designed for two-isoform splicing events with a focus on exon skipping, but in principle also applicable for mutual exclusion, intron-retaining, alternative poly-A site, 3’ splice site and 5’ splice site.
- Differential momentum genes (DMG): This task is to quantify the proportions of unspliced and spliced RNAs in each gene and each cell. Similar to DAS, the DMG is a principled selection of genes that capture heterogeneity in transcriptional kinetics between cell groups, e.g., cell types, or continuous cell covariates, hence may enhance the RNA velocity analyses by focusing on dynamics informed genes.
Though we highly recommend using BRIE v2 for a coherent way for splicing phenotype selection, BRIE1 CLI (MCMC based & gene feature only) is still available but the CLIs are changed to brie1 and brie1-diff.
Questions and Issues¶
If you find any technical issues in the codes, we will appreciate your report. Please write them in the GitHub issues: https://github.com/huangyh09/brie/issues
If you have other specific questions on using BRIE, feel free to get in touch with us: yuanhua <at> hku.hk
- Code on GitHub: https://github.com/huangyh09/brie
- Preprocessed splicing events annotations (GFT/GFF3): http://sourceforge.net/projects/brie-rna/files/annotation/
- Example datasets: https://github.com/huangyh09/brie-tutorials
- All releases: https://pypi.org/project/brie/#history
- Issue reports: https://github.com/huangyh09/brie/issues
- Yuanhua Huang and Guido Sanguinetti. BRIE2: computational identification of splicing phenotypes from single-cell transcriptomic experiments. Genome Biology, 2021; 22(1):251.
- Yuanhua Huang and Guido Sanguinetti. BRIE: transcriptome-wide splicing quantification in single cells. Genome Biology, 2017; 18(1):123.