For the dual-channel datasets, (Spellman, PramilaL, PramilaS), LoessOnly methods show large average correlation, in contrast to the low number of highly correlated pairs, noted for the same methods (previous paragraph).
Based on this rationale, data from yeast two hybrid methods are sufficiently consistent to allow for intra species comparisons (between different experiments) and inter species comparisons, while data from affinity purification mass spectrometry methods show large differences even within intra species comparisons.
When the underlying distribution is bimodal (Fig. 3d), all three methods show large underestimation, although ABC continues performing best for n >40, showing smaller AREs.
Other methods showed larger gold nanoparticle sizes between 3 and 15 nm (Figures 2c, 3b for LPRD and Figures 2d, 3c for US).
The methods showed large differences in prediction accuracy but the supervised method was found to perform best, despite the parameters of the unsupervised methods having been optimized.
As said before, all methods showed large bias if events were rare, particularly if accompanied by other problems, such as strong selection and also a large treatment effect.
Also, the combined method shows larger effect in the oil-wet core when compared to the water-wet core.
The TEC derived with Ne-Quick and IRI-01 corrected options show better agreement with GPS-TEC while the TEC from IRI-01 method shows larger deviations.
However, undiluted samples analyzed by the DCC method showed large standard deviations of repeatability and SCC values lower than those by the DMSCC or FSCC methods, probably because of the high solids content in ovine milk.
