Comparison of binary adjacency weights of the same gene in two different networks

Compute the pairwise Hamming or Jaccard distance between binary edge weights of the same genes in two different network topologies (denoted as adj_mat_qry and adj_mat_sbj).

network_dist_pairwise_genes(
  adj_mat_qry,
  adj_mat_sbj,
  dist_type = "hamming",
  print_message = TRUE
)

Arguments

adj_mat_qry	a binary adjacency matrix generated with network_rescale and network_make_binary.
adj_mat_sbj	a binary adjacency matrix with the same genes as in adj_mat_qry, but with differnt binary edge weights generated with network_rescale and network_make_binary.
dist_type	a distance method that shall be applied on the binary values for each gene. Available options are: dist_type = "hamming": computes the hamming.distance for each gene between the two input matrices dist_type = "jaccard": computes the jaccard for each gene between the two input matrices
print_message	shall massages be printed? Default is print_message = TRUE.

Author

Hajk-Georg Drost

Examples

## Import and rescale PIDC network
# path to PIDC output file
pidc_output <- system.file('beeline_examples/PIDC/outFile.txt', package = 'edgynode')
# import PIDC specific output
pidc_parsed <- pidc(pidc_output)
#> Repairing names...
#> New names:
#> * `` -> ...1
#> * `` -> ...2
#> * `` -> ...3
#> * `` -> ...4
#> * `` -> ...5
#> * ...
#Set diagonal values
diag(pidc_parsed) <- 1
# rescaling PIDC output
pidc_rescaled <- network_rescale(pidc_parsed)
pidc_binary_adj_mat <- network_make_binary(pidc_rescaled, threshold = "median")
#> network_make_binary() applies the median value over all values in the input matrix an uses [45.73] as cut-off threshold to transform the input weighted adjacency matrix into a binary adjacency matrix.
# compute hamming distances for each gene between input matrices
network_dist_pairwise_genes(pidc_binary_adj_mat, 
pidc_binary_adj_mat, dist_type = "hamming")
#> - adj_mat_qry: nrow = (19) and ncol(19)
#> - adj_mat_sbj: nrow = (19) and ncol(19)
#> The Hamming Distances for each gene between the two input matrices are computed.
#>         UGR_qry_vs_UGR_sbj WT1mKTS_qry_vs_WT1mKTS_sbj 
#>                          0                          0 
#>     GATA4_qry_vs_GATA4_sbj WT1pKTS_qry_vs_WT1pKTS_sbj 
#>                          0                          0 
#>     FOXL2_qry_vs_FOXL2_sbj     DMRT1_qry_vs_DMRT1_sbj 
#>                          0                          0 
#>       DKK1_qry_vs_DKK1_sbj     RSPO1_qry_vs_RSPO1_sbj 
#>                          0                          0 
#>   CTNNB1_qry_vs_CTNNB1_sbj       WNT4_qry_vs_WNT4_sbj 
#>                          0                          0 
#>     NR0B1_qry_vs_NR0B1_sbj         SRY_qry_vs_SRY_sbj 
#>                          0                          0 
#>     NR5A1_qry_vs_NR5A1_sbj         DHH_qry_vs_DHH_sbj 
#>                          0                          0 
#>       PGD2_qry_vs_PGD2_sbj         AMH_qry_vs_AMH_sbj 
#>                          0                          0 
#>       FGF9_qry_vs_FGF9_sbj       SOX9_qry_vs_SOX9_sbj 
#>                          0                          0 
#>       CBX2_qry_vs_CBX2_sbj 
#>                          0 

# compute jaccard distances for each gene between input matrices
network_dist_pairwise_genes(pidc_binary_adj_mat, 
pidc_binary_adj_mat, dist_type = "jaccard")
#> - adj_mat_qry: nrow = (19) and ncol(19)
#> - adj_mat_sbj: nrow = (19) and ncol(19)
#> The Jaccard Similarity Coefficients for each gene between the two input matrices are computed.
#>         UGR_qry_vs_UGR_sbj WT1mKTS_qry_vs_WT1mKTS_sbj 
#>                          1                          1 
#>     GATA4_qry_vs_GATA4_sbj WT1pKTS_qry_vs_WT1pKTS_sbj 
#>                          1                          1 
#>     FOXL2_qry_vs_FOXL2_sbj     DMRT1_qry_vs_DMRT1_sbj 
#>                          1                          1 
#>       DKK1_qry_vs_DKK1_sbj     RSPO1_qry_vs_RSPO1_sbj 
#>                          1                          1 
#>   CTNNB1_qry_vs_CTNNB1_sbj       WNT4_qry_vs_WNT4_sbj 
#>                          1                          1 
#>     NR0B1_qry_vs_NR0B1_sbj         SRY_qry_vs_SRY_sbj 
#>                          1                          1 
#>     NR5A1_qry_vs_NR5A1_sbj         DHH_qry_vs_DHH_sbj 
#>                          1                          1 
#>       PGD2_qry_vs_PGD2_sbj         AMH_qry_vs_AMH_sbj 
#>                          1                          1 
#>       FGF9_qry_vs_FGF9_sbj       SOX9_qry_vs_SOX9_sbj 
#>                          1                          1 
#>       CBX2_qry_vs_CBX2_sbj 
#>                          1