Tradeoff between more cells and higher read depth for single-cell RNA-seq spatial ordering analysis of the liver lobule

Abstract As single-cell experiments generate increasingly more cells at reduced sequencing depths, the value of a higher read depth may be overlooked. Using data from two contrasting single-cell RNA-seq protocols that lend themselves to having either higher read depth (Smart-seq) or many cells (MARS-seq) we evaluate the trade-offs in the context of pseudo-spatial reconstruction of the liver lobule. Overall, we find gene expression profiles after spatial-reconstruction analysis are highly reproducible between datasets. Smart-seq’s higher sensitivity and read-depth allows analysis of lower expressed genes and isoforms. Our analysis emphasizes the importance of selecting a protocol based on the biological questions and features of interest. Additionally, by performing subsampling analyses we evaluate trade-offs for each protocol and illustrate that optimizing the balance between sequencing depth and number of cells within a protocol is important for efficient use of resources.