[Paper Review] Exponential scaling of single-cell RNA-seq in the last decade

Valentine Svensson, Roser Vento‐Tormo+1 more|arXiv (Cornell University)|Apr 5, 2017

Single-cell and spatial transcriptomics166 citations

TL;DR

A perspective detailing the key technological developments that have driven the exponential increase in single-cell RNA-sequencing data over the past decade. It discusses how improvements in protocols and technologies enable scalable cell-type surveys.

ABSTRACT

The ability to measure the transcriptomes of single cells has only been feasible for a few years, and is becoming an extremely popular assay. While many types of analysis and questions can be answered using single cell RNA-sequencing, a central focus is the ability to survey the diversity of cell types within a sample. Unbiased and reproducible cataloging of distinct cell types requires large numbers of cells. Technological developments and protocol improvements have fuelled a consistent exponential increase in the numbers of cells studied in single cell RNA-seq analyses. In this perspective, we will highlight the key technological developments which have enabled this growth in data.

Motivation & Objective

• Motivate the study of single-cell RNA-seq growth by highlighting its demand for large cell surveys.
• Identify the major technological and methodological developments enabling scalable single-cell transcriptomics.
• Explain how unbiased, reproducible cataloging of cell types benefits from increasing cell numbers analyzed.

Proposed method

• Review and synthesize technological developments and protocol improvements that contributed to growth in single-cell RNA-seq studies.
• Discuss how these innovations impact data scale, diversity, and accessibility for cell-type discovery.

Experimental results

Research questions

• RQ1 What technological developments have enabled exponential scaling in single-cell RNA-seq over the last decade?
• RQ2 How do protocol improvements affect the ability to survey diverse cell types in a given sample?
• RQ3 What are the implications of increasing cell numbers for unbiased and reproducible cell-type cataloging?

Key findings

• Technological and protocol advances have consistently fueled exponential growth in single-cell RNA-seq data.
• Growth in data enables more comprehensive surveys of cellular diversity within samples.
• Unbiased cataloging of distinct cell types benefits from analyzing large numbers of cells.