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. 2019 May 17;10:2209. doi: 10.1038/s41467-019-09990-5

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© The Author(s) 2019

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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 7 — Complete deconvolution pipeline reveals bias when fractions are compared to blood counts. The results of the pipeline for dataset GSE20300 (a), GSE77434 (b), and E-MTAB-6413 (c). d Simulation dataset where cell types had different RNA content. In the middle, predicted proportions are compared against fraction of cell types RNA in the sample. On the right, predicted proportions are compares against actual cell type counts