Most of what makes cells functionally distinct happens at the post-transcriptional level, but we spent a decade obsessing over transcriptomics. scRNAseq is powerful precisely because it's incomplete... it forces us to think about what it doesn't capture.

Early protocols were… character building. Manual cell picking. FACS into 96-well plates. Massive amplification bias. If you think your current dataset is noisy, imagine doing your PhD on 96 cells and praying your ERCCs behave.

Means scRNAseq is basically the same age as many current PhD students. The first full scRNA-seq transcriptomes were published in 2009 (Tang et al.), when “single cell” still meant one cell, hand-picked, not 100k droplet runs.

1/  Mapping quantitative data to color www.nature.com/articles/nm...