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Table 1 Overview of GeneWalk and alternative methods used for systematic comparison of gene function relevance scoring. The alternative methods were selected based on prevalence of usage or characteristic model features

From: GeneWalk identifies relevant gene functions for a biological context using network representation learning

   Requirements  
Method Objective Input type GO annotations Gene network Defining model characteristic
GeneWalk Gene function relevance scoring Gene list Yes Yes Network representation learning (cosine similarity)
PANTHER Gene set enrichment Gene list Yes No Overrepresentation analysis (Fisher Exact test)
GeneMANIA Gene function prediction (binary classification) Gene list Yes Yes Network label propagation algorithm
GGEA Gene set enrichment Quantitative expression score for all genes Yes Yes Gene set overrepresentation analysis accounting for gene network
GSEA Gene set enrichment Quantitative expression score for all genes Yes No Gene set enrichment analysis (permutation score test)
MGSA Gene set relevance scoring Gene list Yes No Bayesian network (posterior probability)
PADOG Gene set enrichment Expression levels for all genes Yes No Pathway Analysis with Down-weighting of Overlapping Genes (permutation score test)
STRING Gene set enrichment Gene list Yes No Overrepresentation analysis (Hypergeometric test)
topGO Gene set enrichment Gene list Yes No Overrepresentation analysis (Fisher Exact test) with decorrelation of parental GO terms