Reference

Inferring gene regulatory network
inferCSN
inferCSN-package	inferCSN: Inferring Cell-Specific Gene Regulatory Network
inferCSN()	Inferring Cell-Specific Gene Regulatory Network
Network processing
weight_filter()	weight_filter
crossweight()	Perform crossweighting
crossweight_params()	estimates min and max values for crossweighting for now assumes uniform cell density across pseudotime/only considers early time this needs to be refined if it's to be useful...
Network visualization
dynamic.networks()	Plot of dynamic networks
contrast.networks()	contrast.networks
network.heatmap()	The heatmap of network
Network evaluation
auc.calculate()	AUC value calculate
acc.calculate()	ACC calculate
Calculate gene rank
calculate.gene.rank()	Calculate and rank TFs in network
Sparse regression model
single.network()	Construct network for single gene
sparse.regression()	Sparse regression model
model.fit()	Fit a sparse regression model
Utils functions
check.parameters()	Check input parameters
coef(<SRM_fit>) coef(<SRM_fit_CV>)	Extracts a specific solution in the regularization path
net.format()	Format weight table
table.to.matrix()	Switch weight table to matrix
filter_sort_matrix()	Filter and sort matrix
normalization()	normalization
parallelize_fun()	Apply function over a List or Vector
prepare.performance.data()	prepare.performance.data
print(<SRM_fit>) print(<SRM_fit_CV>)	Prints a summary of model.fit
predict(<SRM_fit>) predict(<SRM_fit_CV>)	Predict Response
Example data
example_matrix	Example matrix data
example_meta_data	Example meta data
example_ground_truth	Example ground truth data