Igniting full-length isoform analysis in single-cell and spatial RNA-seq data with FLAMESv2

Long-read single-cell RNA-sequencing enables the profiling of RNA isoform expression and alternative splicing at the single cell level. However, diverse single-cell technologies and sparse isoform data demand flexible, accurate, processing and analysis tools. Here we introduce FLAMESv2 , a highly modular and protocol-agnostic R/Bioconductor package for long-read singlecell RNA-seq data processing. FLAMESv2 supports a wide range of single-cell and spatial experimental protocols, is highly configurable and scalable, allowing seamless multi-sample analysis and provides versatile visualisation and analysis outputs. We demonstrate FLAMESv2 compatibility with both dropletbased and combinatorial barcoding single-cell methods, as well as spatial transcriptomics workflows. Applying FLAMESv2 to in vitro differentiation of stem cells into neurons, we identify celltypes, differentiation trajectories, expression of annotated and novel isoforms and isoform expression diversity and heterogeneity within individual cells. FLAMESv2 provides a comprehensive, flexible approach to analysing long-read single-cell RNA-sequencing, unlocking this powerful methodology for RNA isoform characterisation.