get_gene_cluster: Gene Clustering

In tinglab/redPATH: Reconstructing the pseudo development time of cell lineages in single cell RNA-Seq data and applications in cancer.

Description

Simple gene cluster on the significant genes sorted matrix (based on dCor and MIC). Can be either HMM matrix or the gene expression matrix

Usage

get_gene_cluster(sorted_matrix, cls_num = 8)

Arguments

sorted_matrix	This can be either the HMM matrix or the sorted gene selection matrix obtained from earlier functions.
cls_num	The number of gene cluster desired

Examples

selected_result <- gene_selection(full_exprs_matrix, redpath_pseudotime, dcor_result, mic_result, threshold = 0.5)
gene_state_result <- calc_all_hmm_diff_parallel(selected_result, cls_num = 2, threadnum = 4) 
inferred_gene_cluster <- get_gene_cluster(sorted_matrix = gene_state_result, cls_num = 2)
heatmap_plot <- plot_heatmap_analysis(sorted_matrix = inferred_gene_cluster, redpath_pseudotime, cell_labels = NULL, gene_cluster = inferred_gene_cluster, input_type = "hmm")

tinglab/redPATH documentation built on May 31, 2019, 10:37 a.m.