# Inferring Cell-Specific Gene Regulatory Network

## Documentation for package ‘inferCSN’ version 1.2.0

- DESCRIPTION file
- Package README

## Help Pages

inferCSN-package | Inferring Cell-Specific Gene Regulatory Network
calculate_accuracy | Calculate Accuracy
calculate_auc | Calculate AUC Metrics
calculate_auprc | Calculate AUPRC Metric
calculate_auroc | Calculate AUROC Metric
calculate_f1 | Calculate F1 Score
calculate_gene_rank | Rank TFs and genes in network
calculate_ji | Calculate Jaccard Index
calculate_metrics | Calculate Network Prediction Performance Metrics
calculate_precision | Calculate Precision Metric
calculate_recall | Calculate Recall Metric
calculate_si | Calculate Set Intersection
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_srm | Sparse regression model
inferCSN | inferring cell-type specific gene regulatory network
inferCSN-method | inferring cell-type specific gene regulatory network
infercsn_logo | The logo of inferCSN
meta_cells | Detection of metacells from single-cell gene expression matrix
network_format | Format network table
network_sift | Sifting network
plot_coefficient | Plot coefficients
plot_coefficients | Plot coefficients for multiple targets
plot_contrast_networks | Plot contrast networks
plot_dynamic_networks | Plot dynamic networks
plot_edges_comparison | Network Edge Comparison Visualization
plot_embedding | Plot embedding
plot_histogram | Plot histogram
plot_network_heatmap | Plot network heatmap
plot_scatter | Plot expression data in a scatter plot
plot_static_networks | Plot dynamic networks
print.infercsn_logo | Print logo
single_network | Construct network for single target gene
subsampling | Subsampling function
weight_sift | Weight sift