Optimization of clone positions and proportion of mutations in each clone followed by filtering on most likely possibility for each mutation and a re-optimization.
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Schrod |
A list of dataframes (one for each sample), generated by the Patient_schrodinger_cellularities() function. |
nclust |
Number of clones to look for (mandatory if prior_center or prior_weight are null) |
prior_center |
Clone coordinates (from another analysis) to be used |
prior_weight |
Prior on the fraction of mutation in each clone |
contamination |
Numeric vector with the fraction of normal cells contaminating the sample |
epsilon |
Stopping condition for the algorithm: what is the minimal tolerated difference of position or weighted between two steps |
optim |
use L-BFS-G optimization from R ("default"), or from optimx ("optimx"), or Differential Evolution ("DEoptim") |
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