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Integrated cross talk on specific cluster analysis

single_integrated_cross_talk.Rd

The function calculates cross-talk between genes involved in communication with a specific cluster/cell type and cluster gene sets

Usage

single_integrated_cross_talk(
  S_list,
  ref,
  A,
  k = 9,
  bin_type = "number",
  cut_par = 9,
  perm_link = "degree",
  perm_weights = "simple",
  mc_cores_perm = 1,
  mc_cores_ct = 1
)

Arguments

S_list

a named list of genes grouped into gene sets, as obtained from `build_S_list()`, plus the reference gene set list

ref

name of the gene set in `S_list` that contains all genes of cluster i involved in the communication with cluster j

A

adjacency matrix of the whole gene network considered (can be a sparseMatrix)

k

number of permutations

bin_type

can be either "number" (suggested), "interval" or "width". See `ggplot2::cut_interval()` for details.

cut_par

number of bin to cut. If set to `NULL`, the function will search for the best cut in 2:15

perm_link

= c("degree", "simple") If the permutation of the link should be degree-conservative ("degree"), or random ("simple")

perm_weights

= c("degree", "simple") If the permutation of the weights should be degree-conservative ("degree"), or random ("simple")

mc_cores_perm

number of thread to be used in permutations

mc_cores_ct

number of threads to be used for cross talk calculation

Value

The function returns a data.frame with the results of ct calculation:

  • S1_name,S2_name: names of gene-set pairs considered

  • c: cross-talk score

  • S1_size,S2_size: number of genes in S1 and S2

  • S1_s2_size,S2_s1_size: number of S1 genes interacting with S2, and vice versa

  • dL: number of links between S1 and S2

  • L: number of possible links between S1 and S2

  • r_c: cross-talk saturation, calculated as `dL/L`

  • u1,u2: sum of the gene weights in S1 and S2, respectively

  • S1,S2: list of interacting genes in S1 and S2, respectively

  • s: cross-talk summary score

  • pA,pU: p-values of the number of links (pA) and weights (pU)

  • p: combined p-value

Details

The function takes as inputs the adjacency matrix of the biological network (`A`), the gene-set list `S_list()` and the name of the gene set that contains the communication genes (`ref`). For each gene-set pair that shows at least a link between them, the function calculates the cross-talk and the statistical evaluation, as described in the paper, using `k` permutations.