GuidedSparseKmeans: GuidedSparseKmeans

In LingsongMeng/GuidedSparseKmeans: Guided Sparse K-means

Description

Guided Sparse K-means

Usage

GuidedSparseKmeans(x, z, K, s, lam, model, nstart = 20, maxiter = 15,
  silence = F)

Arguments

x	Gene expression matrix, n*p (rows for subjects and columns for genes).
z	One phenotypic variable from clinical dataset, a vector.
K	Number of clusters.
s	The boundary of l1n weights, a vector.
lam	The intensity of guidance.
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.

Details

Guided Sparse K-means integrating clinical dataset with gene expression dataset.

Value

m lists, m is the length of parameter s. Each list is consisting of

weights	weight for each feature, zero weight means the feature is not selected.
clusters	cluster results.
object	objective value.
bound	a boundary of l1n weights
R2.per	R-squared or pseudo R-squared between phenotypic variable and expression value of each gene, a vector.

Author(s)

Lingsong Meng

LingsongMeng/GuidedSparseKmeans documentation built on May 11, 2020, 12:29 a.m.