Systematic comparative analysis of single cell RNA-sequencing methods
Sean K. Simmons,
Monika S. Kowalczyk,
Cynthia C. Hession,
Nemanja D. Marjanovic,
Travis K Hughes,
Marc H Wadsworth,
Lan T. Nguyen,
John Y. H. Kwon,
Amanda J. Kedaigle,
Alex K. Shalek,
Joshua Z. Levin
Posted 09 May 2019
bioRxiv DOI: 10.1101/632216
Posted 09 May 2019
A multitude of single-cell RNA sequencing methods have been developed in recent years, with dramatic advances in scale and power, and enabling major discoveries and large scale cell mapping efforts. However, these methods have not been systematically and comprehensively benchmarked. Here, we directly compare seven methods for single cell and/or single nucleus profiling from three types of samples – cell lines, peripheral blood mononuclear cells and brain tissue – generating 36 libraries in six separate experiments in a single center. To analyze these datasets, we developed and applied scumi, a flexible computational pipeline that can be used for any scRNA-seq method. We evaluated the methods for both basic performance and for their ability to recover known biological information in the samples. Our study will help guide experiments with the methods in this study as well as serve as a benchmark for future studies and for computational algorithm development.
- Downloaded 12,708 times
- Download rankings, all-time:
- Site-wide: 182 out of 100,819
- In genomics: 30 out of 6,251
- Year to date:
- Site-wide: 323 out of 100,819
- Since beginning of last month:
- Site-wide: 526 out of 100,819
Downloads over time
Distribution of downloads per paper, site-wide
- 20 Oct 2020: Support for sorting preprints using Twitter activity has been removed, at least temporarily, until a new source of social media activity data becomes available.
- 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!