Plot heatmap with annotations for combo metrics data

Plots a heatmap for metrics data (e.g., "xc50", "x_inf") covering both Single Agents and Combinations. Rows are sorted alphabetically by the primary drug, prioritizing Single Agent conditions first, followed by combinations sorted by co-treatment name and concentration.

Usage

pheatmap_with_anno_combo_metrics(
  dt_metrics,
  dt_metrics_capped = NULL,
  normalization_type = "GR",
  metric = "x_mean",
  fit_source = "gDR",
  hm_title = NA,
  colors_vec = NULL,
  no_breaks = 50,
  cluster_rows = FALSE,
  cluster_cols = TRUE,
  distfun = compute_distances,
  annotation_col = NULL,
  annotation_colors = NULL,
  max_hm_lbl_length = .get_setting("MAX_HM_LBL_LENGTH")
)

Arguments

dt_metrics

data.table representing data from the metrics assay, outputted by gDRutils::convert_se_assay_to_dt. Must contain DrugName, DrugName_2, cotrt_value, and CellLineName.

dt_metrics_capped

data.table representing data from the "Metrics" assay, the same as dt_metrics but with capped values with gDRutils::cap_assay_infinities

normalization_type

string with normalization types to be selected one of: "GR" ("GRvalue") or "RV" ("RelativeViability")

metric

string name of the metric; one of: "xc50" ("GR50" or "IC50" - respectively depending on normalization_type), "x_max" ("GR Max" or "E Max") or "x_mean" ("GR Mean" or "RV Mean"); but the values from any numeric column can be displayed.

fit_source

string source name for metrics

hm_title

string plot title

colors_vec

character vector of colors (valid name or hex) used in heatmap; note that the first color will be assigned to the min value, and the last one - to the max

no_breaks

numeric number of breaks on scale used for mapping values to colors

cluster_rows

logical flag whether rows should be clustered; the dendrogram will not be shown for the matrix with any dimension greater than 200.

cluster_cols

logical flag whether columns should be clustered; the dendrogram will not be shown for the matrix with any dimension greater than 200.

distfun

function used to compute the distance (dissimilarity) between both rows and columns; used for the dendrogram when cluster_rows or cluster_cols is set to TRUE the default is compute_distances using Spearman method.

annotation_col

data.table that specifies the annotations shown above the heatmap. Each row defines the features for a specific column. The columns in the data and in the annotation are matched using corresponding names from the required CellLineName column. Note that color schemes takes into account if variable is continuous or discrete.

annotation_colors

named list for specifying annotation_col and annotation_row track colors manually; note list is named with annotation name (column names of annotation_row - without DrugName and column names of annotation_col - without CellLineName), each list item is named vector with valid color name for each value described in annotation_row and in annotation_col - respectively. Not described elements will be colored in default.

max_hm_lbl_length

numeric value for the maximum number of characters in the label; if set to Inf, no trimming will be performed; for better readability, it is recommended to use the default number.

Value

A named list with elements:

• data a list containing the information visualized in the heatmap:

  • matrix data shown in the heatmap for the selected metric.

  • annotation_row a table with row annotations (auto-generated).

  • annotation_col a table with column annotations, if provided.

• heatmap the pheatmap object.

Author

Bartosz Czech czech.bartosz@external.gene.com

Examples

mae <- gDRutils::get_synthetic_data("combo_matrix_small")
se <- mae[[gDRutils::get_supported_experiments("combo")]]
dt_metrics <- gDRutils::convert_se_assay_to_dt(se = se,
                                               assay_name = "Metrics")

output <- pheatmap_with_anno_combo_metrics(dt_metrics = dt_metrics,
                                           normalization_type = "RV",
                                           metric = "x_mean")
hm_1 <- output[["heatmap"]]
patchwork::wrap_elements(hm_1[["gtable"]])


annotation_manual <- data.table::data.table(
  CellLineName =
    c("cellline_AA", "cellline_GB", "cellline_HB"),
  mut_A = c(0, 1, 1),
  mut_B = c("yes", "yes", "no")
)
annotation_map <- list(
  mut_A = c("1" = "coral", "0" = "cadetblue"),
  mut_B = c("yes" = "black", "no" = "grey90")
)

output <- pheatmap_with_anno_combo_metrics(dt_metrics = dt_metrics,
                                           metric = "ec50",
                                           normalization_type = "GR",
                                           annotation_col = annotation_manual,
                                           annotation_colors = annotation_map,
                                           hm_title = get_hm_title(
                                             normalization_type = "GR",
                                             metric = "EC50 for combo data ",
                                             dataset_name = "Combo data"))



mae <- gDRutils::get_synthetic_data("combo_triple")
se <- mae[[gDRutils::get_supported_experiments("combo")]]
dt_metrics <- gDRutils::convert_se_assay_to_dt(se = se,
                                               assay_name = "Metrics",
                                               merge_additional_variables = TRUE)

output <- pheatmap_with_anno_combo_metrics(dt_metrics = dt_metrics,
                                           normalization_type = "RV",
                                           metric = "x_mean")
hm_4 <- output[["heatmap"]]
patchwork::wrap_elements(hm_4[["gtable"]])