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. 2020 Mar 5;21:57. doi: 10.1186/s13059-020-1950-6

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© 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.

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Fig. 2 — Contamination in a human-mouse cell mixture dataset. a The total number of UMIs aligned specifically to the mouse or human genome is plotted for each droplet. b The proportion of counts for mouse genes in human cells is highly correlated to the average expression of these genes across all mouse cells indicating that the amount of contamination for each gene is proportional to how highly that gene is expressed in the contaminating cell population. c Similarly, the proportion of counts for human genes in the mouse cells is highly correlated to the average expression of those genes across all human cells. d While each droplet is predicted to contain a single cell, the median percentage of contamination for human and mouse cells is 1.09% and 2.75%, respectively. The range of contamination is 0.43–45.09% indicating the need for contamination estimation for each individual cell