# COndition SpecIfic sub-NEtwork

## Documentation for package ‘COSINE’ version 2.1

- DESCRIPTION file.

## Help Pages

COSINE-package | COndition SpecIfic subNEtwork identification
choose_lambda | Choose the most appropriate weight parameter lambda
cond.fyx | Compute the ECF-statistics measuring the differential correlation of gene pairs
COSINE | COndition SpecIfic subNEtwork identification
DataSimu | Simulation of the six datasets and the case dataset
diff_gen | Calculate the F-statistics and ECF-statistics
diff_gen_for3 | Generate the F-statistics and ECF-statistics for the comparison of three datasets
diff_gen_PPI | Generate the scaled node score and scaled edge score for nodes and edges in the background network
f.test | To get the F-statistics for each gene
GA_search | Use genetic algorithm to search for the globally optimal subnetwork
GA_search_PPI | Run genetic algorithm to search for the PPI sub-network
get_components_PPI | Get all the components (connected clusters) of the sub-network
get_quantiles | Get the five quantiles of the weight parameter lambda
get_quantiles_PPI | Get the five quantile values of lambda for analysis of gene expression and PPI network data
PPI | The protein protein interaction network data
random_network_sampling_PPI | To sample random sub-network from the PPI data
scaled_edge_score | The scaled ECF statistics of all the edges
scaled_node_score | The scaled ECF-statistics of all the edges
Score_adjust_PPI | To adjust the score of the selected PPI sub-network using random sampling
score_scaling | To get the normalzied F-statistics and ECF-statistics
set1_GA | Result of genetic algorithm search for simulated data set1
set1_scaled_diff | The standardized F-statistics and ECF-statistics for the comparison between simulated data1 and the control data
set1_unscaled_diff | The unstandardized F-statistics and ECF-statistics of simulated dataset 1
simulated_data | The simulated data sets used in the paper