multiClust (version 1.0.2)

avg_probe_exp: Function to produce a matrix containing the average expression of each gene probe within each sample cluster.

Description

Function to produce a matrix containing the average expression of each gene probe within each sample cluster.

Usage

avg_probe_exp(sel.exp, samp_cluster, data_name, cluster_type = "HClust",
  distance = "euclidean", linkage_type = "ward.D2",
  probe_rank = "SD_Rank", probe_num_selection = "Fixed_Probe_Num",
  cluster_num_selection = "Fixed_Clust_Num")

Arguments

sel.exp

Object containing the numeric selected gene expression matrix. This object is an output of the probe_ranking function.

samp_cluster

Object vector containing the samples and the cluster number they belong to. This is an output of the cluster_analysis function.

data_name

String indicating the cancer type and name of the dataset being analyzed. This name will be used to label the sample dendrograms and heatmap files.

cluster_type

String indicating the type of clustering method used in the cluster_analysis function. "Kmeans" or "HClust" are the two options.

distance

String describing the distance metric uses for HClust in the cluster_analysis function. Options include one of "euclidean", "maximum", manhattan", "canberra", "binary", or "minkowski".

linkage_type

String describing the linkage metric used in the cluster_analysis function. Options include "ward.D2", "average", "complete", "median", "centroid", "single", and "mcquitty".

probe_rank

String indicating the feature selection method used in the probe_ranking function. Options include "CV_Rank", "CV_Guided", "SD_Rank", and "Poly".

probe_num_selection

String indicating the way in which probes were selected in the number_probes function. Options include "Fixed_Probe_Num", "Percent_Probe_Num", and "Adaptive_Probe_Num".

cluster_num_selection

String indicating how the number of clusters were determined in the number_clusters function. Options include "Fixed_Clust_Num" and "Gap_Statistic".

Value

• Returns an object matrix with the average mean expression for each probe in each sample cluster. Also outputs the object to a text file.

See Also

number_clusters, number_probes, probe_ranking, cluster_analysis

Examples

# Produce matrix of average expression of each probe in each cluster
# 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 for Kmeans parameters
kmeans_analysis <- cluster_analysis(sel.exp=sel.data, cluster_type="Kmeans",
    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")
# Call function for average matrix expression calculation
avg_matrix <- avg_probe_exp(sel.exp=sel.data, samp_cluster=kmeans_analysis,
    data_name="GSE2034 Breast", cluster_type="Kmeans", distance=NULL,
    linkage_type=NULL, probe_rank="CV_Rank",
    probe_num_selection="Fixed", cluster_num_selection="Fixed_Clust_Num")