DoDiffusionMap: Construct diffusion map and select root cell
In ChenWeiyan/LandSCENT: Landscape Single Cell Entropy

Description Usage Arguments Value References Examples

This function constructs diffusion map with highly variable genes and identify the root cell with cell cluster and signaling entropy rate

DoDiffusionMap(
  Integration.l,
  mean_gap = 1,
  sd_gap = 1,
  root = c("cell", "state"),
  num_comp = 3,
  k = 30
)

`Integration.l`	Typically, it is the output from `InferLandmark` function
`mean_gap`	The threshold for HVG gene selection based on the mean expression level. Default value is 1
`sd_gap`	The threshold for HVG gene selection based on the expression level's standard deviation. Default value is 1
`root`	Define the root of the trajectory. `cell` indicates the root is the cell with the highest SR value among all cells; `state` indicates the root is the cell with the highest SR value within the highest inferred potency state
`num_comp`	A numeric. The dimension of diffusion map, which is related to the following plot generation. Default is 3
`k`	Number of nearest neighbors to consider. Default is 30

An updated list objects, add three elements:

DM A diffusion map object

DMEigen The diffusion components of the diffusion map

root The index of root cell for generating diffusion map plots

Teschendorff AE, Tariq Enver. Single-cell entropy for accurate estimation of differentiation potency from a cell’s transcriptome. Nature communications 8 (2017): 15599. doi: 10.1038/ncomms15599.

Teschendorff, Andrew E., Peter Sollich, and Reimer Kuehn. Signalling entropy: A novel network-theoretical framework for systems analysis and interpretation of functional omic data. Methods 67.3 (2014): 282-293. doi: 10.1016/j.ymeth.2014.03.013.

## Not run: 
data(Example.m)
data(net13Jun12.m)
Integration.l <- DoIntegPPI(exp.m = Example.m[, c(1:58,61:84,86:98,100)], ppiA.m = net13Jun12.m)
data(SR.v)
Integration.l$SR <- SR.v
InferPotency.o <- InferPotency(Integration.l)
DoDM.o <- DoDiffusionMap(InferPotency.o)
## End(Not run)