Figure 7.

An illustration (in 2D) of how our method for grouping samples on the 3D surface works. In this illustration, each circle represents a sample; samples having similar values in feature space are given the same color. The algorithm proceeds as follows: starting with a radius R, identify discs of radius R that have minimum average distance (in feature space) between elements in the disc. Replace the best non-overlapping discs with the sample in the center of each disc. Repeat, each time reducing the size of the disc. When complete, there will still be samples not contained in a disc. Merge those into neighboring discs if their distance from the center sample is less than a threshold T. The resulting center samples are used for surface prediction. In all results, R= 4Å and T=.25.

Cipriano et al. BMC Bioinformatics 2012 13:314   doi:10.1186/1471-2105-13-314
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