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. 2015 Sep 17;16(1):708. doi: 10.1186/s12864-015-1912-7

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© Parsons et al. 2015

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. 6 — Clustering of Expression measures in 4 SEQC samples and 2 in-silico replicate samples across participating sites: The close agreement between modeled (Cm, Dm) counts and actual counts (A, B, C, D) at sites numbered 1–6 supports the validity of assumptions used to model Cm and Dm counts. Euclidian distance measures between samples show that the various samples are of greater distance from one another, while the in-silico modeled samples are most similar to the correct corresponding sample