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# Introduction
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Confidence maps are complementary maps generated from common EM maps and aim to provide statistical significance measures for the corresponding densities. They are based on the false discovery rate of voxels, i.e. the expected amount of voxels that are declared erroneous for signal but are actually background noise. They can be visualised like any other map in molecular visualisation softwares.
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Confidence maps provide a way to set a objective contour level and at the same time give an error criterion associated with the density. Especially building and interpretation of difficult features like small molecule ligands, water molecules and ions is facilitated. The usage is not limited to near-atomic resolution maps, as confidence maps from lower resolution sub-tomogram averages have been shown to provide similar advantages for density interpretation, especially when working with noisy data generated from a small amount of sub-tomograms.
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The statistical framework allows the incorporation of local resolution and atomic model information in order to increase the power of the test procedure. |
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