Single-cell RNA sequencing (scRNA-seq) is largely reliant on the existence of a reference genome to which the new sequencing reads can be aligned to. Unfortunately, that rules out 99.9% of organisms! “Single-cell transcriptomics for the 99.9% of species without reference genomes” proposes a new computational pipeline called Kmermaid that relies on the power of k-mers in an attempt to obviate the need for a reference genome when using scRNA-seq. The first step processes the reads into amino acid translation frames, because “protein sequences are more evolutionarily conserved than the underlying DNA.” The last step is to use these k-mer representations to search in a database of expression profiles for common cell types to make the final prediction. This constitutes an exciting new paradigm for alignment-free cross-species prediction of cell types that throws out far less data

• Uncategorized