Inferring Cell-Specific Gene Regulatory Network

---

Documentation for package ‘inferCSN’ version 1.1.7

• DESCRIPTION file.

Help Pages

inferCSN-package	_*inferCSN*_: *infer*ring *C*ell-*S*pecific gene regulatory *N*etwork
%ss%	Value selection operator
as_matrix	Convert sparse matrix into dense matrix
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
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_srm	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
matrix_to_table	Switch matrix to network table
meta_cells	Detection of metacells from single-cell gene expression matrix
network_format	Format network table
network_sift	Sifting network
normalization	Normalize numeric vector
parallelize_fun	Parallelize a function
pearson_correlation	Correlation and covariance calculation for sparse matrix
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
predict.srm	Predicts response for a given sample
predict.srm_cv	Predicts response for a given sample
print.srm	Prints a summary of 'sparse_regression'
print.srm_cv	Prints a summary of 'sparse_regression'
r_square	R^2 (coefficient of determination)
simulate_sparse_matrix	Generate a simulated sparse matrix for single-cell data testing
single_network	Construct network for single target gene
sparse_cor	Safe correlation function which returns a sparse matrix without missing values
sparse_cov_cor	Fast correlation and covariance calcualtion for sparse matrices
sparse_regression	Fit a sparse regression model
split_indices	Split indices.
subsampling	Subsampling function
table_to_matrix	Switch network table to matrix
weight_sift	Weight sift