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. 2019 Feb 6;20:66. doi: 10.1186/s12859-019-2641-8

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© The Author(s). 2019

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 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.

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Fig. 4 — Hierarchical clustering at the level of individual gene expression for SEQC project data. Panel a – results following quantile normalization (QN); b – DESeq/DESeq2; c – Shambhala with Affymetrix microarray Q-dataset; d – Shambhala with Illumina HiSeq 2000 Q-dataset. Panel e – legend explaining origin of biosamples A, B, C, D and experimental platform in the project. To facilitate the visual analysis of the hierarchical clustering dendrogram, we selected randomly only 20 profiles out of 1324 that were obtained using the Illumina HiSeq 2000 (GPL11154) platform. More detailed view of the dendrograms is given in Additional file 6