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Table 1 Types of networks and characteristics

From: Comparison of co-expression measures: mutual information, correlation, and model based indices

Network type Used here Examples Variable Ease of estimation Utility for modeling Adjacencies Used in GO
    types         discussed enrichment
            this article analysis
      GRN Reduce Direct Time Nonlin. Sign   
Correlation network Yes WGCNA [5] Numeric Easy Yes Yes No Maybe No Yes unsignedA Yes
            signedA Yes
            TOM Yes
Polynomial or Yes WGCNA [5] Numeric Moderate Yes Yes No Maybe Yes No poly R 2 No
Spline regression            spline R 2 No
Mutual information network Yes ARACNE Discretized Moderate Yes Not clear No Maybe Yes No ASU No
   [9], RELNET numeric,         AUV1 No
   [6, 28], CLR categorical         AUV2 Yes
   [26], MRNET          ARACNE Yes
   [27], MIC [35]          ARACNE0.2 Yes
            ARACNE0.5 Yes
            CLR Yes
            MRNET Yes
            RELNET Yes
            MIC Yes
Boolean network No Boolean network [71] Dichoto-mized numeric Moderate Yes Not clear Yes Yes NA NA No No
Probabilistic network No Bayesian network [72, 73] Any Hard Yes Not clear Yes Yes Yes Yes No No
  1. For each network method, the table reports what kinds of biological insights can be gained and what kind of data can be analyzed. Column “GRN” indicates whether the network has been (or can be) used for studying gene regulatory networks. Column “Reduce” indicates whether the method has been used for reducing high dimensional data (e.g. via modules and their representatives). Column “Direct” indicates whether the the network can encode directional information. Column “time” indicates whether the network method is suited for studying time series data. Column “Nonlin. ” indicates whether the network can capture non-linear relationships between pairs of variables (represented as nodes). Column “Sign” indicates whether the network adjacency provides information on the sign of the relationship between two variables, e.g. a correlation coefficient can take on positive and negative values. The table entry “NA” stands for not applicable. Adjacencies discussed in this article: unsignedA: unsigned bicor; signedA: signed bicor; TOM: TOM transformed signed bicor; ASU: AMI,SymmetricUncertainty; AUV1: AMI,UniversalVersion 1; AUV2: AMI,UniversalVersion 2; ARACNE: ARACNE, ε = 0 ; ARACNE0.2: ARACNE, ε = 0. 2 ; ARACNE0.5: ARACNE, ε = 0. 5.