# Example 1: HClust Analysis
# Load in a data file
data_file <- system.file("extdata", "GSE2034.normalized.expression.txt",
package="multiClust")
data <- input_file(input=data_file)
# Choose 300 genes to select for
gene_num <- number_probes(input=data_file, data.exp=data, Fixed=300,
Percent=NULL, Adaptive=NULL)
# Choose the "CV_Rank" Method for gene ranking
sel.data <- probe_ranking(input=data_file, probe_number=300,
probe_num_selection="Fixed_Probe_Num", data.exp=data, method="CV_Rank")
# Choose a fixed cluster number of 3
clust_num <- number_clusters(data.exp=data, Fixed=3, gap_statistic=NULL)
# Call function using HClust parameters
hclust_analysis <- cluster_analysis(sel.exp=sel.data, cluster_type="HClust",
seed = NULL, distance="euclidean", linkage_type="ward.D2",
gene_distance="correlation", num_clusters=3,
data_name="GSE2034 Breast", probe_rank="CV_Rank",
probe_num_selection="Fixed_Probe_Num",
cluster_num_selection="Fixed_Clust_Num")
# Example 2: Kmeans Analysis
# Call function for Kmeans parameters
kmeans_analysis <- cluster_analysis(sel.exp=sel.data, cluster_type="Kmeans",
seed = 1, distance=NULL, linkage_type=NULL, gene_distance=NULL,
num_clusters=3, data_name="GSE2034 Breast",
probe_rank="CV_Rank", probe_num_selection="Fixed_Probe_Num",
cluster_num_selection="Fixed_Clust_Num")
Run the code above in your browser using DataLab