| InfiniumClust {InfiniumPurify} | R Documentation |
Tumor sample clustering from Infinium 450k array data
Description
Clustering of tumor samples into subtypes accounting for tumor purity.
Usage
InfiniumClust(tumor.data, purity, K, maxiter = 100, tol = 0.001)
Arguments
tumor.data |
numeric matrix of beta values for tumor samlpes. The rownames of tumor.data should be probe names of Infinium 450k array, and colnames should be names of tumor samples. |
purity |
purities for tumor samples. Could be estimated by |
K |
the number of clusters. |
maxiter |
the maximum number of iterations allowed. Default is 100. |
tol |
tolerance for convergence of EM iterations. Default is 0.001. |
Details
An EM based statistical method for subtype classification based on DNA methylation data, while adjusting for tumor purity.
Value
InfiniumClust returns a list consisting oflikelihood tol.ll and membership matrix Z.
tol.ll |
total log-likelihood of converged EM algorithm. |
Z |
the membership matrix, where row corresponds to tumor samples and column corresponds to K clusters. |
Author(s)
Xiaoqi Zheng xqzheng@shnu.edu.cn and Hao Wu hao.wu@emory.edu
References
W. Zhang, H. Feng, H. Wu and X. Zheng (2016). Tumor purity improves cancer subtype classification from DNA methylation data. Submitted.
Examples
## load example data
data(beta.emp)
normal.data <- beta.emp[,1:21]
tumor.data <- beta.emp[,22:31]
## estimate tumor purity
purity <- getPurity(tumor.data = tumor.data,tumor.type= "LUAD")
## cluster tumor samples accounting for tumor purity
out <- InfiniumClust(tumor.data,purity,K=3, maxiter=5, tol=0.001)