Single-Cell Omics for Transcriptome CHaracterization (SCOTCH): isoform-level characterization of gene expression through single-cell long-read RNA sequencing

The advent of long-read single-cell transcriptome sequencing (lrsc-RNA-Seq) represents a significant leap forward in single-cell genomics, enabling a deeper exploration into the complexity of cell type-specific transcriptomic variations. Few existing computational methods exist specifically for long-read data, yet we propose two assertions in the current study: (1) with the introduction of R10 flowcells by Oxford Nanopore, previous computational methods designed to handle high sequencing error rates become less relevant; (2) the prevailing approach to use paired short-read to compile "barcode space" (candidate barcode list) for long-read to de-multiplex are no longer necessary. Instead, computational methods should now shift focus on harnessing the unique benefits of long reads to analyze transcriptome complexity, in the absence of short reads. In this context, we introduce a comprehensive suite of computational methods named Single-Cell Omics for Transcriptome CHaracterization (SCOTCH). Our method is compatible with the single-cell library preparation platform from both 10X Genomics and Parse Biosciences, thus facilitating the analysis of special cell populations, such as neurons, hepatocytes or cardiac cells, which cannot be assayed by the 10X Genomics platform. We specifically re-formulated the transcript mapping problem with a compatibility matrix and addressed the multiple-mapping issue using probabilistic inference from unique-mapping reads. By framing the identification of novel isoforms as a graph community detection problem and introducing a statistical analysis pipeline, our approach allows the discovery of novel isoforms as well as the detection of differential isoform usage and isoform switching events between cell populations. We evaluated SCOTCH through analysis of real data from human peripheral blood mononuclear cells (PBMC) with short-read library protocols (10X Genomics, Parse Biosciences) on the Illumina platform and long-read (10X Genomics, Parse Biosciences) library protocols on the Oxford Nanopore platform with R9 and R10 flowcells.