Description Usage Arguments Details Value Author(s)
View source: R/GuidedSparseKmeans.KLam.R
Selection of Tuning Parameter K and lam in Guided Sparse K-means
1 2 | GuidedSparseKmeans.KLam(x, z, pre.K = NULL, s.one, model, nstart = 20,
maxiter = 15, silence = F)
|
x |
Gene expression matrix, n*p (rows for subjects and columns for genes). |
z |
One phenotypic variable from clinical dataset, a vector. |
pre.K |
Pre-knowledge of the number of clusters. |
s.one |
A proper value of the boundary of l1n weights. |
model |
The model fitted to obtain R2, please select model from 'linear', 'logit', 'exp', 'polr','cox'. |
nstart |
Specify the number of starting point for K-means. |
maxiter |
Maximum number of iteration. |
silence |
Output progress or not. |
Select tuning parameter K using gap statistics and tuning parameter lam using sensitivity analysis in Guided Sparse K-means integrating clinical dataset with gene expression dataset.
A list consisting of
K.select |
value of selected K. |
lam.select |
value of selected lam. |
R2.per |
R-squared or pseudo R-squared between phenotypic variable and expression value of each gene, a vector. |
ARI.Cs |
Adjusted ARI values for cluster results. |
Jaccard.gene |
Jaccard index values for gene selection results. |
Lingsong Meng
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