plot_heatmap_analysis: Heatmap Analysis

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

Description

Comprehensive heatmap plot function with gene cluster and cell type labels.

Usage

plot_heatmap_analysis(sorted_matrix, pseudo_time, cell_labels = NULL,
  gene_cluster = NULL, heading = "HEATMAP", input_type = "hmm")

Arguments

sorted_matrix	This can be either the HMM matrix or the sorted gene selection matrix obtained from earlier functions.
pseudo_time	Pseudo development time
cell_labels	Defaults to NULL. The cell type labels.
gene_cluster	Defaults to NULL. It can be automatically caluclated with defualt gene cluster of 8. Or user can define the inferred gene cluster results using hierarchical clustering (get_gene_cluster) or by other means. Note that the input must match for the input matrix (ie gene / hmm)
heading	Plot title
input_type	"hmm" or "gene". Please specify type of sorted matrix input to the function.

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 = 8)
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.