construct_receptor_tf_matrix: Construct a matrix containing receptor-tf probability scores
In Pinlyu3/LRLoop: Two-way communication between cells

Construct a matrix containing receptor-tf probability scores

construct_receptor_tf_matrix(
  weighted_networks,
  receptors,
  rtf_cutoff = 0.99,
  damping_factor = 0.5,
  receptors_as_cols = FALSE
)

`weighted_networks`	A list of two weighted networks sig and gr (signaling network and gene regulatory network), in data frame/tibble with columns "from", "to" and "weight".
`receptors`	A list of receptor gene symbols.
`rtf_cutoff`	Receptor-tf scores lower than the "rtf_cutoff" quantile will be set to 0.
`damping_factor`	A number between 0 and 1, the probability that the random walker in the PPR algorithm will continue the walk on the graph.
`receptors_as_cols`	"TRUE" or "FALSE", indicates whether receptors should be in columns of the matrix and targets in rows or vice versa.