molnet (version 0.1.0)

molnet_settings: Create global settings variable for molnet pipeline

Description

Function that allows creating a global `settings` variable used in the start_pipeline function. Default parameters can be changed within the function call.

Usage

molnet_settings(
  correlation_method = "pearson",
  print_graph_info = TRUE,
  reduction_method = "p_value",
  handling_missing_data = "all.obs",
  p_value_adjust_method = "BH",
  reduction_alpha = 0.05,
  r_squared_cutoff = 0.6,
  cut_vector = seq(0.2, 0.8, by = 0.05),
  n_threads = 1,
  parallel_chunk_size = 10^6,
  saving_path = tempdir(),
  save_individual_graphs = TRUE,
  save_combined_graphs = TRUE,
  save_drug_targets = TRUE,
  save_correlation_filename = NULL,
  python_executable = "python3",
  max_path_length = 3,
  int_score_mode = "auto",
  ...
)

Arguments

correlation_method

Correlation method used for graph generation. One of (`pearson`, `spearman`, `kendall`).

print_graph_info

Boolean. Print a summary of the reduced graph to console after generation?

reduction_method

Reduction method for reducing networks. One of `p_value`, 'pickHardThreshold' or `pickHardThreshold_alternative`. Can be a single character string if the same for all layers, else a named list mapping layer names to methods. Layers may be omitted if a method is mapped to `default`.

handling_missing_data

Specifying the handling of missing data during correlation computation. Use "all.obs" or "pairwise.complete.obs". Argument is passed to cor. Can be a single character string if the same for all layers, else a named list mapping layer names to methods. Layers may be omitted if a method is mapped to `default`.

p_value_adjust_method

String of the correction method applied to p-values. Passed to p.adjust. ("holm", "hochberg", "hommel", "bonferroni",

reduction_alpha

A number indicating the significance value for correlation p-values during reduction. Not-significant edges are dropped.

r_squared_cutoff

A number indicating the desired minimum scale free topology fitting index R^2 for reduction using pickHardThreshold.

cut_vector

A vector of hard threshold cuts for which the scale free topology fit indices are to be calculated during reduction with pickHardThreshold.

n_threads

Number of threads for parallel computation of p-values during p-value reduction.

parallel_chunk_size

Number of p-values in smallest work unit when computing in parallel during network reduction with method `p_value`.

saving_path

Path to save outputs of `molnet` functions. Default is a temporary directory.

save_individual_graphs

Boolean specifying if individual graphs should be saved during start_pipeline

save_combined_graphs

Boolean specifying if combined graphs should be saved during start_pipeline

save_drug_targets

Boolean specifying if drug targets should be saved during start_pipeline

save_correlation_filename

File name for saving correlation adjacency matrices in generate_individual_graphs.

python_executable

Path to Python executable used for computing simple paths.

max_path_length

Integer of maximum length of simple paths to include in computation.

int_score_mode

One of `auto`, `sequential` or `ray`. Whether to compute interaction score in parallel using the Ray python library or sequentially. When `auto` it depends on the graph sizes.

...

Supply additional settings.

Value

Named list of settings

Examples

# NOT RUN {
settings <- molnet::molnet_settings(correlation_method = "spearman", max_path_length = 3,
                                    handling_missing_data = list(
                                      default = "pairwise.complete.obs",
                                      mrna = "all.obs"
                                    ),
                                    reduction_method = "p_value"
                                   )

# }