Rank TFs and genes in network
Examples
data(example_matrix)
network_table <- inferCSN(example_matrix)
#> ℹ [2025-10-16 02:36:37] Running for <dense matrix>.
#> ◌ [2025-10-16 02:36:37] Checking input parameters...
#> ℹ [2025-10-16 02:36:37] Using `L0` sparse regression model
#> ℹ [2025-10-16 02:36:37] Using 1 core
#> ℹ [2025-10-16 02:36:37] Building results
#> ✔ [2025-10-16 02:36:37] Run done.
head(calculate_gene_rank(network_table))
#> gene rank_value regulator
#> 1 g18 0.05883983 TRUE
#> 2 g17 0.05873281 TRUE
#> 3 g9 0.05869090 TRUE
#> 4 g5 0.05863236 TRUE
#> 5 g7 0.05811175 TRUE
#> 6 g6 0.05756879 TRUE
head(calculate_gene_rank(network_table, regulators = "g1"))
#> gene rank_value regulator
#> 1 g1 0.46396396 TRUE
#> 2 g2 0.18784178 FALSE
#> 3 g18 0.13390621 FALSE
#> 4 g17 0.02111819 FALSE
#> 5 g5 0.02038973 FALSE
#> 6 g9 0.01973099 FALSE
head(calculate_gene_rank(network_table, targets = "g1"))
#> gene rank_value regulator
#> 1 g1 0.46396396 FALSE
#> 2 g18 0.22091630 TRUE
#> 3 g2 0.09045695 TRUE
#> 4 g17 0.03444956 TRUE
#> 5 g9 0.01902045 TRUE
#> 6 g16 0.01740632 TRUE