Inferring Cell-Specific Gene Regulatory Network

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Documentation for package ‘inferCSN’ version 1.0.8

• DESCRIPTION file.

Help Pages

inferCSN-package	_*inferCSN*_: *infer*ring *C*ell-*S*pecific gene regulatory *N*etwork
as_matrix	Convert dgCMatrix into a dense matrix
calculate_acc	Calculate accuracy value
calculate_auc	Calculate AUPRC and AUROC values
calculate_gene_rank	Rank TFs and genes in network
check_sparsity	Check sparsity of matrix
coef.srm	Extracts a specific solution in the regularization path
coef.srm_cv	Extracts a specific solution in the regularization path
example_ground_truth	Example ground truth data
example_matrix	Example matrix data
example_meta_data	Example meta data
filter_sort_matrix	Filter and sort matrix
fit_sparse_regression	Fit a sparse regression model
inferCSN	*infer*ring *C*ell-*S*pecific gene regulatory *N*etwork
inferCSN-method	*infer*ring *C*ell-*S*pecific gene regulatory *N*etwork
log_message	Print diagnostic message
network_format	Format network table
network_sift	Sifting network
normalization	Normalize numeric vector
parallelize_fun	Parallelize a function
plot_contrast_networks	Plot contrast networks
plot_dynamic_networks	Plot dynamic networks
plot_embedding	Plot embedding
plot_network_heatmap	Plot network heatmap
plot_scatter	Plot expression data in a scatter plot
plot_static_networks	Plot dynamic networks
plot_weight_distribution	Plot weight distribution
predict.srm	Predicts response for a given sample
predict.srm_cv	Predicts response for a given sample
print.srm	Prints a summary of 'fit_sparse_regression'
print.srm_cv	Prints a summary of 'fit_sparse_regression'
r_square	R^2 (coefficient of determination)
single_network	Construct network for single target gene
sparse_regression	Sparse regression model
table_to_matrix	Switch network table to matrix