surv_analysis: Function to produce Kaplan-Meier Survival Plots of selected...

In nlawlor/multiClust: multiClust: An R-package for Identifying Biologically Relevant Clusters in Cancer Transcriptome Profiles

Description

Function to produce Kaplan-Meier Survival Plots of selected gene expression data.

Usage

surv_analysis(samp_cluster, clinical, survival_type = "RFS", 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

samp_cluster	Object vector containing the samples and the cluster number they belong to. This object is an output of the cluster_analysis function.
clinical	String indicating the name of the text file containing patient clinical information. The file should be a data frame consisting of two columns. The first column contains the patient survival time information in months. The second column indicates occurrence of a censorship (0) or an event (1).
survival_type	String specifying the type of survival event being analyzed. Examples include "Disease-free survival (DFS)", "Overall Survival (OS)", "Relapse-free survival (RFS)", etc.
data_name	String indicating the name to be used to label the plot.
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 use 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_Probee_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

Produces a pdf image of a Kaplan-Meier Survival Plot with Cox Survival P Value. Also returns an object containing the cox survival P value.

Author(s)

Alec Fabbri, Nathan Lawlor

See Also

number_clusters, number_probes, probe_ranking, cluster_analysis, coxph

Examples

# 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")
# Load the clinical outcome file
clin_file <- system.file("extdata", "GSE2034-RFS-clinical-outcome.txt",
    package="multiClust")
# Example of Calling surv_analysis function
surv <- surv_analysis(samp_cluster=kmeans_analysis, clinical=clin_file,
    survival_type="RFS", data_name="GSE2034 Breast", cluster_type="Kmeans",
     distance=NULL, linkage_type=NULL, probe_rank="CV_Rank",
     probe_num_selection="Fixed_Probe_Num",
     cluster_num_selection="Fixed_Cluster_Num")

nlawlor/multiClust documentation built on May 16, 2019, 8:12 p.m.