canopy.cluster.Mstep {Canopy} | R Documentation |
M-step of EM algorithm for multivariate clustering of SNAs. Used in
canopy.cluster
.
canopy.cluster.Mstep(pG, R, X, Tau_Kplus1)
pG |
matrix of posterior probability of cluster assignment for each mutation |
R |
alternative allele read depth matrix |
X |
total read depth matrix |
Tau_Kplus1 |
proportion mutation cluster that is uniformly distributed to capture noise |
List of bic, converged Mu, Tau, and SNA cluster assignment.
Yuchao Jiang yuchaoj@wharton.upenn.edu
data(AML43) R = AML43$R; X = AML43$X num_cluster = 4 # Range of number of clusters to run num_run = 6 # How many EM runs per clustering step Tau_Kplus1=0.05 # Proportion of noise component Mu.init=cbind(c(0.01,0.15,0.25,0.45),c(0.2,0.2,0.01,0.2)) # initial value # of centroid canopy.cluster=canopy.cluster(R = R, X = X, num_cluster = num_cluster, num_run = num_run, Mu.init = Mu.init, Tau_Kplus1=Tau_Kplus1)