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. 2020 Sep 4;21:221. doi: 10.1186/s13059-020-02126-9

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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. 2 — Validation of lung tissue scRNA-Seq reference matrix. a Boxplots of estimated cell type fractions for single-cells from the lung MCA1 10X atlas, which were annotated as epithelial (Epi), endothelial (Endo), fibroblast (Fib), and immune cell (IC). The number of single cells annotated to each cell type is given. Cell type fractions were estimated using RPC with an expression reference defined over 4 cell types (epithelial, endothelial, fibroblast, and immune cell) using the SmartSeq2 scRNA-Seq data from MCA1. b Left: Barplots depicting the relative fractions of single-cells annotated to each single-cluster (labeled on y-axis) which were predicted to be epithelial, endothelial, fibroblast, or immune cell (labeled by different colors) based on the cell type fraction estimates obtained in a. Right: Barplot displaying the overall accuracy of using RPC+expression reference to correctly classify each single-cell type. c As b, but now for using RPC+expression reference on the 10X human data from Lambrecht et al. and for a total 8 cell types as determined in that study. d Scatterplots of the true cell type fractions (y-axis) vs. the estimated cell type fractions (x-axis) in Lambrecht et al. data as obtained via RPC+expression reference on simulated bulk lung tissue samples, generated via in silico mixtures of 1000 single cells. Mixtures were generated from all 8 cell types as shown in c, and estimated cell type fractions were obtained for total epithelial, endothelial, fibroblast, and immune cell fractions, as shown