# Inferring Cell-Specific Gene Regulatory Network

## 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