COndition SpecIfic sub-NEtwork


[Up] [Top]

Documentation for package ‘COSINE’ version 2.1

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