sc-SPLASH provides ultra-efficient reference-free discovery in barcoded single-cell sequencing

High-throughput single-cell RNA-sequencing (scRNA-seq) analyses typically begin with (pseudo-)alignment, through the lens of annotated gene models, and aimed at detecting differential gene expression. Such methods miss transcriptome diversity generated by other mechanisms such as splicing and V(D)J recombination and are blind to sequences missing from imperfect reference genomes. Here, we present sc-SPLASH, a highly efficient pipeline that extends our SPLASH framework for statistics-first, reference-free discovery to barcoded scRNA-seq (10x Chromium) and spatial transcriptomics (10x Visium). Along with sc-SPLASH, we also present BKC, an optimized tool for preprocessing and k-mer counting in barcoded data. sc-SPLASH rediscovers known biology, including V(D)J recombination and cell-type-specific alternative splicing in human and trans-splicing in tunicate (Ciona), and when applied to spatial transcriptomics, detects sequence variation, including tumor-specific somatic mutation. Most significantly, we show the potential for new biological discovery with sc-SPLASH by applying it to sponge (Spongilla) and tunicate (Ciona), and uncover secreted repeat proteins expressed in immune-type cells; the sponge genes were absent from the reference assembly. sc-SPLASH provides a powerful alternative tool for exploring transcriptomes that is applicable to the breadth of life's diversity.