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. 2016 Dec 20;11:66. doi: 10.1186/s13062-016-0169-7

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© The Author(s) 2016

Open Access This 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 — Empirical False Discovery Rate (eFDR). We estimate an eFDR by dividing the number of differential expression calls in inter-site A-vs-A and C-vs-C comparisons by the number of calls in A-vs-C comparisons. The left panel shows the original results for q-value thresholding only (no additional processing or filters). In the middle panel, hidden confounders have been removed by svaseq. In the right panel, additional filters have also been applied. Plots for various methods of expression estimation are shown along the x-axis, with methods for differential expression calling indicated by colour