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Forseti : a mechanistic and predictive model of the splicing status of scRNA-seq reads

2024; Oxford University Press; Volume: 40; Issue: Supplement_1 Linguagem: Inglês

10.1093/bioinformatics/btae207

1367-4811

Dongze He, Yuan Gao, Spencer Skylar Chan, Natalia Quintana-Parrilla, Rob Patro,

Extracellular vesicles in disease

Short-read single-cell RNA-sequencing (scRNA-seq) has been used to study cellular heterogeneity, cellular fate, and transcriptional dynamics. Modeling splicing dynamics in scRNA-seq data is challenging, with inherent difficulty in even the seemingly straightforward task of elucidating the splicing status of the molecules from which sequenced fragments are drawn. This difficulty arises, in part, from the limited read length and positional biases, which substantially reduce the specificity of the sequenced fragments. As a result, the splicing status of many reads in scRNA-seq is ambiguous because of a lack of definitive evidence. We are therefore in need of methods that can recover the splicing status of ambiguous reads which, in turn, can lead to more accuracy and confidence in downstream analyses.