Add a data modality for SNF generation

This function will add a modality as an affinity matrix for subsequent fusion to the object. To note: all of the modalities need to have the same number of rows, i.e., samples!

Usage

add_snf_data_modality(object, data, data_name, params = NULL)

Arguments

object

The underlying class, see SimilarityNetworkFusion().

data

matrix or data.table. The data to transform into adjacency data and add to the class. Any data supplied will be assumed to be samples x features. The provided data type can be a data.table (for categorical and/or mixed types) or a matrix (for continous types). If you provide a data.table, the function will assume the first column are the sample identifiers. Please ensure that setting.

data_name

String. The data modality name.

params

Optional List. If you wish to overwite the already set up parameters for SNF, see params_snf(). If NULL, the settings from within the object will be used. If not NULL, the new parameters will be used for this modality specifically and only for this modality!

Value

The class with added adjacency matrix for this data.

Examples

# add a categorical clinical modality to a continuous one
set.seed(42)
continuous <- matrix(rnorm(120), nrow = 12, ncol = 10)
rownames(continuous) <- sprintf("sample_%02i", 1:12)
colnames(continuous) <- sprintf("feature_%i", 1:10)
clinical <- data.table::data.table(
  sample_id = rownames(continuous),
  sex = factor(sample(c("M", "F"), 12, replace = TRUE)),
  stage = factor(sample(c("I", "II", "III"), 12, replace = TRUE))
)
object <- SimilarityNetworkFusion(
  data = continuous,
  data_name = "continuous",
  snf_params = params_snf(k = 3L)
)
object <- add_snf_data_modality(object, clinical, data_name = "clinical")
dim(get_snf_adjcacency_mat(object, name = "clinical"))
#> [1] 12 12