RAD: A Read-structure Agnostic Demultiplexer for Single-Cell Long-Read Sequencing and Analysis
Single-cell long-read sequencing (LRS) techniques enable the analysis of full transcript sequences within a cell. However, the high error rate inherent to LRS introduces computational challenges for parsing information like cell barcode, and custom workflows are often required to handle complex read layouts, such as split combinatorial barcodes. We introduce an error-robust, read-structure agnostic demultiplexer (RAD). In RAD, users can easily specify read structure, such as adapter sequence and barcode relative position, and can rapidly extract these elements for each read. In addition to finding the barcode, RAD implements efficient barcode correction strategies for scenarios of knowing or not knowing the full barcode whitelist or having paired short-read single-cell sequencing data for a short whitelist. In synthetic and real-world benchmarks, RAD is faster and achieves significantly higher sensitivity than existing pipelines while having comparable precision. We show RAD can be applied to high-definition long-read spatial transcriptomic data and demonstrate single cell and spatial analysis of B cell isotype and secretion states.