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. 2020 Jul 10;21:170. doi: 10.1186/s13059-020-02083-3

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© The Author(s) 2020

Open AccessThis 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. 6 — Evaluation of DEG identification. DEG was identified using MAST for a the JURKAT_293T dataset and b the 10X_5CL dataset, where x-axis shows the false number of DEGs identified from a homogeneous population (293T and A549 cell lines were used, respectively) and y-axis shows the averaged overlaps of DEGs identified by scRNA-seq data to that of bulk RNA-seq for all the combination of cell lines in the dataset. c For a pair of cell lines in the 10X_5CL dataset, genes were grouped into 10 intervals ranked by their FC values. For example, interval 1 is top 10% genes ranked by FC. The overlap between bulk and single-cell DEGs identified using MAST were calculated for 10 combinations of cell lines for each interval. Box plots show the median (center line), interquartile range (hinges), and 1.5 times the interquartile range (whiskers) for the 10 overlap values