AutoPipe (version 0.1.6)

Supervised_Cluster_Heatmap: Produce a Heatmap using a Supervised clustering Algorithm

Description

This function produces a plot with a Heatmap using a supervised clustering algorithm which the user choses. with a the mean Silhouette width plotted on the right top corner and the Silhouette width for each sample on top. On the right side of the plot the n highest and lowest scoring genes for each cluster will added. And next to them the coressponding pathways (see Details)

Usage

Supervised_Cluster_Heatmap(groups_men, gene_matrix,
method="PAMR",TOP=1000,TOP_Cluster=150,
show_sil=FALSE,show_clin=FALSE,genes_to_print=5,
print_genes=FALSE,samples_data=NULL,colors="RdBu",
GSE=FALSE,topPaths=5,db="c2",plot_mean_sil=FALSE,stats_clust =NULL,threshold=2)

Arguments

groups_men

the data frame with the group clustering that the function Groups_Sup or top_supervised (2. place on the list) returns with the data about each sample and its coressponding cluster.

gene_matrix

the matrix of n selected genes that the function Groups_Sup returns

method

the method to cluster of Clustering. The default is "PAMR" which uses the pamr library. other methods are SAM and our own "EXReg" (see details)

TOP

the number of the top genes to take. the default value is 1000.

TOP_Cluster

a numeric variable for the number of genes to include in the clusters. Default is 150.

show_sil

a logical value that indicates if the function should show the Silhouette width for each sample. Default is FALSE.

show_clin

a logical value if TRUE the function will plot the clinical data provided by the user. Default value is FALSE.

genes_to_print

the number of genes to print for each cluster. this function adds on the right side. of the heatmap the n highest expressed genes and the n lowest expressed genes for each cluster. Default value is 5.

print_genes

a logical value indicating if or not to plot the TOP genes for each cluster.Default value is FALSE.

samples_data

the clinical data provided by the user to plot under the heatmap. it will be plotted only if show_clin is TRUE. Default value is NULL. see details for format.

colors

the colors for the Heatmap. The function RColorBrewer palletes.

GSE

a logical variable that indicates wether to plot thr Gene Set Enrichment Analysis next to the heatmap. Default value is FALSE.

topPaths

a numerical value that says how many pathways the Gene Set Enrichment plots should contain fo each cluster. Default value is 5.

db

a value for the database for the GSE to be used. Default value is "c1". the paramater can one of the values: "c1","c2","c3",c4","c5","c6","c7","h". See the broad institue GSE GSE webpage for further information in each dataset.

plot_mean_sil

A logical value. if TRUE the function plots the mean of the Silhouette width for each cluster number or gap statistic.

stats_clust

A vector with the mean Silhouette widths or gap statistic for the number of clusters. The first value should be for 2 Clusters. 2nd is for 3 clusters and so on.

threshold

the threshhold for the pam analysis default is 2.

Details

sample data should be a data.frame with the sample names as rownames and the clinical triats as columns. each trait must be a numeric variable.

Examples

# NOT RUN {
##load the org.Hs.eg Library
library(org.Hs.eg.db)
## load data
data(rna)
me_x=rna
## calculate best number of clusters and
res<-AutoPipe::TopPAM(me_x,max_clusters = 6, TOP=100)
me_TOP=res[[1]]
number_of_k=res[[3]]
File_genes=Groups_Sup(me_TOP, me=me_x, number_of_k,TRw=-1)
groups_men=File_genes[[2]]
me_x=File_genes[[1]]
o_g<-Supervised_Cluster_Heatmap(groups_men = groups_men, gene_matrix=me_x,
    method="PAMR",show_sil=TRUE,print_genes=TRUE,threshold=0,
    TOP = 100,GSE=FALSE,plot_mean_sil=TRUE,stats_clust=res[[2]])

# }