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Construction of artificial “bulk” gene expression data

MS Max Schelker
SF Sonia Feau
JD Jinyan Du
NR Nav Ranu
EK Edda Klipp
GM Gavin MacBeath
BS Birgit Schoeberl
AR Andreas Raue
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The artificial “bulk” gene expression data that was used for testing the deconvolution approach was generated from single-cell RNA sequencing data by aggregating reads from all cell barcodes for each patient sample. As single-cell and conventional bulk sequencing differ in their quantification biases, we cannot assume that single-cell-based RGEPs are applicable for deconvolution of conventional bulk sequencing data. Therefore, to apply the deconvolution based on single-cell RGEPs, conventional sequencing must be adapted to closely mimic the quantification process in single-cell sequencing, however, without the cell barcoding that would be problematic in a clinical trial setting.

Copyright and License information: The Author(s) ©2017
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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