Generally speaking, invasive measurement methods are more accurate than non-invasive methods, but provide more limited spatial information; therefore, a combination of both is desirable, preferably supplemented by simulations.
The MRC emphasise the need for robust and rigorous evaluation of complex interventions, promoting the use of experimental methods, but providing information on some of the alternatives to the conventional randomised controlled trial and highlighting situations in which a trial is impractical or undesirable [ 4].
The FETI method, however, is not only a coupling method but provides a powerful solver design.
MLH is a robust method but provides homozygosity-by-state (HBS) information only and is therefore of limited use in inbreeding and admixture studies as has been previously reported [ 5, 6, 14].
The new model not only inherits the versatility of the TCD method but providing an essential assessment of the statistical size effect.
We briefly describe the methods below, but provide further detail of all modelling methods and all input parameter values, sources and assumptions in Text S1.
The main advantages of our approach stem from having a compact empirically-learned model that characterizes the stochastic nature of the microstructure, which not only makes reconstruction more computationally efficient than existing methods, but also provides insight into morphological complexity.
Simulation results show that the proposed detector not only reduces computational complexity compared to existing methods but also provides superior performance, particularly when the signal to noise ratio is low.
It not only overcomes the limitations of other methods but also provides an absolute and quantitative expression measurement [ 16, 17].
Our MDL approach belongs to this class of parsimony-based methods, but it provides a way to place the cost of recombination and of homoplasy on an equal footing, that of information complexity.
