Decontamination of ambient RNA in single-cell RNA-seq with DecontX
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Date
2020-03-05
Authors
Yang, Shiyi
Corbett, Sean E.
Koga, Yusuke
Wang, Zhe
Johnson, W. Evan
Yajima, Masanao
Campbell, Joshua David
Version
Published version
OA Version
Citation
S. Yang, S.E. Corbett, Y. Koga, Z. Wang, W.E. Johnson, M. Yajima, J.D. Campbell. 2020. "Decontamination of ambient RNA in single-cell RNA-seq with DecontX.." Genome Biol, Volume 21, Issue 1, 57. https://doi.org/10.1186/s13059-020-1950-6
Abstract
Droplet-based microfluidic devices have become widely used to perform single-cell RNA sequencing (scRNA-seq). However, ambient RNA present in the cell suspension can be aberrantly counted along with a cell's native mRNA and result in cross-contamination of transcripts between different cell populations. DecontX is a novel Bayesian method to estimate and remove contamination in individual cells. DecontX accurately predicts contamination levels in a mouse-human mixture dataset and removes aberrant expression of marker genes in PBMC datasets. We also compare the contamination levels between four different scRNA-seq protocols. Overall, DecontX can be incorporated into scRNA-seq workflows to improve downstream analyses.
Description
License
© The Author(s). 2020. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.