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. 2009 Oct 23;38(1):e4. doi: 10.1093/nar/gkp853

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© The Author(s) 2009. Published by Oxford University Press.

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Figure 4. — Plots showing the ability of MMBGX to recover gene-level log expression values from simulated human Gene array data. (A) The scatterplot shows that the model implementation recovers the simulated expression values, μ_gc, for non-multi-mapping probesets accurately; (B) the scatterplot shows that the expression for multi-mapping probesets with one or more probes that uniquely match the intended transcript is also well-estimated; (C) the scatterplot shows that the expression for multi-mapping probesets with no probes that uniquely match the intended transcript has higher variance and shrinkage towards the mean at low and high levels of expression, μ_gc; (D) the density lines show that the shrunk estimates of μ_gc (i.e. those hailing from multi-mapping probesets with no single-match probes) have a higher MCSE than the non-shrunk estimates (i.e. hailing from multi-mapping probesets with at least one single-match probe).