canopy.cluster.Mstep {Canopy} | R Documentation |

## M-step of EM algorithm for multivariate clustering of SNAs

### Description

M-step of EM algorithm for multivariate clustering of SNAs. Used in
`canopy.cluster`

.

### Usage

```
canopy.cluster.Mstep(pG, R, X, Tau_Kplus1)
```

### Arguments

`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 |

### Value

List of bic, converged Mu, Tau, and SNA cluster assignment.

### Author(s)

Yuchao Jiang yuchaoj@wharton.upenn.edu

### Examples

```
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)
```

[Package

*Canopy*version 1.3.0 Index]