Expectation Maximization algorithm

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Description

Optimization of clone positions and proportion of mutations in each clone.

Usage

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EM.algo(Schrod, nclust = NULL, prior_center = NULL, prior_weight = NULL,
  contamination, epsilon = 10^(-2), optim = "default")

Arguments

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")

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