getClustNum: Get estimation of optimal clustering number

In xlucpu/MOVICS: Multi-Omics integration and VIsualization in Cancer Subtyping

Description

This function provides two measurements (i.e., clustering prediction index [CPI] and Gap-statistics) and aims to search the optimal number for multi-omics integrative clustering. In short, the peaks reach by the red (CPI) and blue (Gap-statistics) lines should be referred to determine 'N.clust'.

Usage

getClustNum(
  data = NULL,
  is.binary = rep(FALSE, length(data)),
  try.N.clust = 2:8,
  center = TRUE,
  scale = TRUE,
  fig.path = getwd(),
  fig.name = "optimal_number_cluster"
)

Arguments

data	List of matrices.
is.binary	A logicial vector to indicate if the subdata is binary matrix of 0 and 1 such as mutation.
try.N.clust	A integer vector to indicate possible choices of number of clusters.
center	A logical value to indicate if the variables should be centered. TRUE by default.
scale	A logical value to indicate if the variables should be scaled. FALSE by default.
fig.path	A string value to indicate the output figure path.
fig.name	A string value to indicate the name of the figure.

Value

A figure that helps to choose the optimal clustering number (argument of 'N.clust') for 'get

CPI possible cluster number identified by clustering prediction index

Gapk possible cluster number identified by Gap-statistics

References

Chalise P, Fridley BL (2017). Integrative clustering of multi-level omic data based on non-negative matrix factorization algorithm. PLoS One, 12(5):e0176278.

Tibshirani, R., Walther, G., Hastie, T. (2001). Estimating the number of data clusters via the Gap statistic. J R Stat Soc Series B Stat Methodol, 63(2):411-423.

Examples

# There is no example and please refer to vignette.

xlucpu/MOVICS documentation built on July 24, 2021, 9:23 p.m.