Display the intersection table summarizing the results from 2 or more datasets

Usage

intersections_table(
  res_list,
  threshold,
  annotation_table,
  col_module_id,
  annotation_level,
  object_of_interest
)

Arguments

res_list: List of dataframes. The results from apply_NeighborFinder() on several datasets
threshold: Numeric. Integer corresponding to the minimum number of datasets in which you want neighbors to have been found
annotation_table: Dataframe. The dataframe gathering the taxonomic or functional module correspondence information
col_module_id: String. The name of the column with the module names in annotation_table
annotation_level: String. The name of the column with the level to be studied. Examples: species, genus, level_1
object_of_interest: String. The name of the bacteria or species of interest or a key word in the functional module definition

Value

Dataframe. Table gathering the intersection of NeighborFinder results from several datasets. The column 'datasets' indicates the datasets in which the same neighbor has been found, the column 'intersections' indicates the number of datasets in which the same neighbor has been found

Examples

data(taxo)
data(data)
data(metadata)
res_CRC_JPN <- apply_NeighborFinder(data$CRC_JPN, object_of_interest = "Escherichia coli", col_module_id = "msp_id", annotation_level = "species")
res_CRC_CHN <- apply_NeighborFinder(data$CRC_CHN, object_of_interest = "Escherichia coli", col_module_id = "msp_id", annotation_level = "species", covar = ~study_accession, meta_df = metadata$CRC_CHN, sample_col = "secondary_sample_accession")
res_CRC_EUR <- apply_NeighborFinder(data$CRC_EUR, object_of_interest = "Escherichia coli", col_module_id = "msp_id", annotation_level = "species", covar = ~study_accession, meta_df = metadata$CRC_EUR, sample_col = "secondary_sample_accession")

intersections_table(res_list = list(res_CRC_JPN, res_CRC_CHN, res_CRC_EUR), threshold = 2, taxo, col_module_id = "msp_id", annotation_level = "species", "Escherichia coli")
#>      node1          module1    node2                 module2   datasets
#> 1 msp_0005 Escherichia coli msp_0103 Clostridium_AQ innocuum n_ 1, n_ 2
#> 2 msp_0005 Escherichia coli msp_0208        Blautia_A faecis n_ 1, n_ 3
#>   intersections   mean_coef
#> 1             2  0.07445512
#> 2             2 -0.12691516