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Table 4 Parameter used to optimize each network-inference algorithms

From: A machine learning approach for the identification of key markers involved in brain development from single-cell transcriptomic data

Network-inference algorithms Parameter optimization settingc
GENIE3-Aa K = “all”, nb.trees = 10,000
GENIE3-Ba K = “sqrt”, nb.trees = 10,000
TIGRESS-Ab scoring = “area”
TIGRESS-Bb scoring = “max”
ARACNE eps = 0.1
BC3NET boot = 10, alpha1 = 0.99, alpha2 = 0.99
SiGN-BN Number of iteration of bootstrap method = 1,000
  1. aGENIE3-A and -B represent two different parameter settings for GENIE3 algorithm used in this study
  2. bTIGRESS-A and -B represent two different parameter settings for TIGRESS algorithm used in this study
  3. cWe used default settings for parameters that are not shown in this table