Gene

Cell type

Biology

Computer science

Computational biology

Exponential growth

Genetics

Transcriptome

Mathematics

RNA-Seq

Mathematical analysis

Cell

Single-cell analysis

Gene expression

Nature Protocols

Here Sarah Teichmann and colleagues provide a Perspective on the exponential scaling of single-cell RNA-sequencing experiments over the last decade, commenting on the methodological developments that have underpinned the advances in this technology. Measurement of the transcriptomes of single cells has been feasible for only a few years, but it has become an extremely popular assay. While many types of analysis can be carried out and various questions can be answered by single-cell RNA-seq, a central focus is the ability to survey the diversity of cell types in a sample. Unbiased and reproducible cataloging of gene expression patterns in distinct cell types requires large numbers of cells. Technological developments and protocol improvements have fueled consistent and exponential increases in the number of cells that can be studied in single-cell RNA-seq analyses. In this Perspective, we highlight the key technological developments that have enabled this growth in the data obtained from single-cell RNA-seq experiments.

Exponential scaling of single-cell RNA-seq in the past decade