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 <monospace>FLAMESv2</monospace> , a highly modular and protocol-agnostic R/Bioconductor package for long-read singlecell RNA-seq data processing. <monospace>FLAMESv2</monospace> 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 <monospace>FLAMESv2</monospace> compatibility with both dropletbased and combinatorial barcoding single-cell methods, as well as spatial transcriptomics workflows. Applying <monospace>FLAMESv2</monospace> 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. <monospace>FLAMESv2</monospace> provides a comprehensive, flexible approach to analysing long-read single-cell RNA-sequencing, unlocking this powerful methodology for RNA isoform characterisation.