Comparative analysis of single-cell RNA sequencing methods
By
Christoph Ziegenhain,
Beate Vieth,
Swati Parekh,
Björn Reinius,
Martha Smets,
Heinrich Leonhardt,
Ines Hellmann,
Wolfgang Enard
Posted 05 Jan 2016
bioRxiv DOI: 10.1101/035758
(published DOI: 10.1016/j.molcel.2017.01.023)
Background: Single-cell RNA sequencing (scRNA‑seq) offers exciting possibilities to address biological and medical questions, but a systematic comparison of recently developed protocols is still lacking. Results: We generated data from 447 mouse embryonic stem cells using Drop‑seq, SCRB‑seq, Smart‑seq (on Fluidigm C1) and Smart‑seq2 and analyzed existing data from 35 mouse embryonic stem cells prepared with CEL‑seq. We find that Smart‑seq2 is the most sensitive method as it detects the most genes per cell and across cells. However, it shows more amplification noise than CEL‑seq, Drop‑seq and SCRB‑seq as it cannot use unique molecular identifiers (UMIs). We use simulations to model how the observed combinations of sensitivity and amplification noise affects detection of differentially expressed genes and find that SCRB‑seq reaches 80% power with the fewest number of cells. When considering cost-efficiency at different sequencing depths at 80% power, we find that Drop‑seq is preferable when quantifying transcriptomes of a large numbers of cells with low sequencing depth, SCRB‑seq is preferable when quantifying transcriptomes of fewer cells and Smart‑seq2 is preferable when annotating and/or quantifying transcriptomes of fewer cells as long one can use in-house produced transposase. Conclusions: Our analyses allows an informed choice among five prominent scRNA‑seq protocols and provides a solid framework for benchmarking future improvements in scRNA‑seq methodologies.
Download data
- Downloaded 17,530 times
- Download rankings, all-time:
- Site-wide: 386
- In genomics: 18
- Year to date:
- Site-wide: 6,633
- Since beginning of last month:
- Site-wide: 6,731
Altmetric data
Downloads over time
Distribution of downloads per paper, site-wide
PanLingua
News
- 27 Nov 2020: The website and API now include results pulled from medRxiv as well as bioRxiv.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!