Compute Signaling Entropy Rate (SR)

Computes single-cell differentiation potency using the signaling entropy rate on a protein interaction network.

Usage

CompSRana(integ.l, local = FALSE)

Arguments

integ.l: Output from DoIntegPPI, containing expMC and adjMC.
local: Logical. If TRUE, returns normalized local entropies. Default FALSE.

Value

List with elements:

SR: Signaling entropy rate (0-1). Higher = higher potency.
inv: Stationary distribution matrix (genes x cells).
locS: Local entropy matrix (genes x cells).
nlocS: Normalized local entropies, or NULL if local = FALSE.

Details

The signaling entropy rate is defined as: $$SR = \sum_j \pi_j S_j / SR_{max}$$

where $\pi_j$ is the stationary distribution and $S_j$ is the local entropy at gene j. $SR_{max}$ is the maximum entropy rate of the network, computed from the largest eigenvalue of the adjacency matrix.

References

Teschendorff AE, Enver T. Nat Commun. 2017;8:15599.

Author

Andrew E Teschendorff, Zaoqu Liu

Examples

if (FALSE) { # \dontrun{
data(net13Jun12.m)
exp <- matrix(rpois(5000 * 50, 5), nrow = 5000)
rownames(exp) <- head(rownames(net13Jun12.m), 5000)
integ <- DoIntegPPI(exp, net13Jun12.m)
sr <- CompSRana(integ)
} # }