Heatmap plot

Heatmap plot

plot_heatmap(mtmutObj, type = "p", cell_ann = NULL, ann_colors = NULL, ...)

Arguments

mtmutObj

an object of class "mtmutObj".

type

a string of plot type, "p" for p-value, "af" for allele frequency.

cell_ann

a data.frame of cell annotation, with rownames as cell barcodes, please refer to pheatmap for details.

ann_colors

a list of colors for cell annotation with cell annotation as names, please refer to pheatmap for details.

...

other parameters for export_df and pheatmap.

Value

The pheatmap output

Examples

# load the data
## Use the example data
f <- system.file("extdata", "mini_dataset.tsv.gz", package = "scMitoMut")

## Create a temporary h5 file
## In real case, we keep the h5 in project folder for future use
f_h5_tmp <- tempfile(fileext = ".h5")

## Load the data with parse_table function
f_h5 <- parse_table(f, sep = "\t", h5_file = f_h5_tmp)

# open the h5f file
x <- open_h5_file(f_h5)
# run the model fit
run_model_fit(x)
#> chrM.200
#> chrM.204
#> chrM.310
#> chrM.824
#> chrM.1000
#> chrM.1001
#> chrM.1227
#> chrM.2285
#> chrM.6081
#> chrM.9429
#> chrM.9728
#> chrM.9804
#> chrM.9840
#> chrM.12889
#> chrM.16093
#> chrM.16147
#>           used  (Mb) gc trigger  (Mb) max used  (Mb)
#> Ncells 2127413 113.7    3221262 172.1  3221262 172.1
#> Vcells 4312878  33.0   10146329  77.5 10123834  77.3
x
#> mtmutObj object
#> -------------------------------------------------
#> h5 file: /tmp/RtmppwH5Ub/file2395d14ab295.h5
#> Available loci: 16
#> Selected loci: 16
#> Available cells: 1359
#> Selected cells: 1359
#> Loci passed the filter: 0
#> filter parameters: 
#> 	min_cell: 1
#> 	model: bb
#> 	p_threshold: 0.05
#> 	alt_count_threshold: 0
#> 	p_adj_method: fdr
# Filter the loci based on the model fit results
x <- filter_loc(x, min_cell = 5, model = "bb", p_threshold = 0.05, p_adj_method = "fdr")

# set the cell annotation
f <- system.file("extdata", "mini_dataset_cell_ann.csv", package = "scMitoMut")
cell_ann <- read.csv(f, row.names = 1)
# Prepare the color for cell annotation
colors <- c(
  "Cancer Epi" = "#f28482",
  Blood = "#f6bd60"
)
ann_colors <- list("SeuratCellTypes" = colors)

# plot the heatmap for p-value
plot_heatmap(x, type = "p", cell_ann = cell_ann, ann_colors = ann_colors, percent_interp = 0.2)

# plot the heatmap for allele frequency
plot_heatmap(x, type = "af", cell_ann = cell_ann, ann_colors = ann_colors, percent_interp = 0.2)

# plot the heatmap for binary mutation
plot_heatmap(x, type = "binary", cell_ann = cell_ann, ann_colors = ann_colors, percent_interp = 0.2)