Perspectives on rigor and reproducibility in single cell genomics
Greg Gibson
Abstract
Over the past ten years, single cell genomics has emerged as a powerful approach to cell biology whose impact relative to bulk tissue genomics can be likened to the transition from light to electron microscopy. Query of PubMed with the term "single cell genomics" reveals over 5,000 papers a year since 2012 for a field that is probably in its early growth phase. Analyses at the single cell level reveal properties of tissues that are barely approachable with bulk methods: the contributions of variable cell type abundance to normal and pathological variation, the identities of the cell-types that explain disease, the molecular basis of intercellular signaling, the trajectories of cells as they mature or senesce, and cellular resolution of regulatory mechanisms, are but five examples. None of this would be possible without the parallel emergence of powerful pipelines and algorithms for data analysis, and advances in high performance computing that facilitate routine handling of many-terabyte-sized datasets. Not a week goes by without the publication of a path-breaking study, job-prospects for trainees are outstanding, and fundamental transitions within the "knowledge machine" of modern biology [1] seem inevitable.