DrDimont (version 0.1.6)

make_layer: Creates individual molecular layers from raw data and unique identifiers

Description

Helper function to transform input data to required pipeline input format. Additionally, the supplied input is checked. Allows easy conversion of raw data into the structure accepted by run_pipeline.

Usage

make_layer(
  name,
  data_groupA,
  data_groupB,
  identifiers_groupA,
  identifiers_groupB
)

Value

Named list containing the supplied data for each group (i.e., the data set for one layer), that can be supplied to run_pipeline and `name` giving the name of the layer. Each sub-list contains the `data` and the `identifiers`.

Arguments

name

[string] Name of the layer.

data_groupA, data_groupB

[data.frame] Dataframe containing raw molecular data of each group (each stratum). Analyzed components (e.g. genes) in columns, samples (e.g. patients) in rows.

identifiers_groupA, identifiers_groupB

[data.frame] Dataframe containing component identifiers (columns) of each component (rows) in the same order as the molecular dataframe of each group. These identifiers are used to (a) interconnect graphs and (b) match drugs to drug targets. Must contain a column `type` which identifies the nature of the component (e.g., "protein")

Examples

data(protein_data)

example_protein_layer <- make_layer(
                             name="protein",
                             data_groupA=protein_data$groupA[, c(-1,-2)],
                             data_groupB=protein_data$groupB[, c(-1,-2)],
                             identifiers_groupA=data.frame(
                                 gene_name=protein_data$groupA$gene_name,
                                 ref_seq=protein_data$groupA$ref_seq),
                             identifiers_groupB=data.frame(
                                 gene_name=protein_data$groupB$gene_name,
                                 ref_seq=protein_data$groupB$ref_seq))