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Table 1 Gene set enrichment analysis of the modules from dual evaluationa

From: Dense module searching for gene networks associated with multiple sclerosis

GO term# contributing genes/ term sizebContributing genescp-valueadj. p-valued
Molecular Function
 Phosphotyrosine residue binding3/18GRB2, MAPK1, MAPK31.916 × 10− 51.674 × 10− 3
 Phosphatidylinositol-4,5-bisphosphate 3-kinase activity4/62CD80, CD86, GRB2, PIK3R23.318 × 10− 51.674 × 10− 3
 Virus receptor activity4/71CD80, CD86, ITGB3, TNFRSF145.667 × 10−51.674 × 10−3
 Phosphatidylinositol bisphosphate kinase activity4/72CD80, CD86, GRB2, PIK3R25.987 × 10−51.674 × 10−3
 Protein phosphorylated amino acid binding3/28GRB2, MAPK1, MAPK27.533 × 10−51.674 × 10−3
Biological Process
 T cell costimulation7/82CD80, CD86, CSK, CTLA4, GRB2, MAP3K14, TNFRSF143.704 × 10−92.113 × 10−6
 Lymphocyte costimulation7/83CD80, CD86, CSK, CTLA4, GRB2, MAP3K14, TNFRSF144.037 × 10−92.113 × 10−6
 JAK-STAT cascade involved in growth hormone signaling pathway4/15MAPK1, MAPK3, STAT3, STAT5A8.415 × 10−82.937 × 10−5
 Growth hormone receptor signaling pathway4/24MAPK1, MAPK3, STAT3, STAT5A6.425 × 10−71.598 × 10− 4
 Cellular response to growth hormone stimulus4/25MAPK1, MAPK3, STAT3, STAT5A7.633 × 10−71.598 × 10−4
Cellular Component
 Nuclear pore5/84KPNB1, NUP153, RAN, SENP2, SNUPN4.311 × 10−63.794 × 10−4
 Clathrin-coated pit4/69AMN, CLTC, EPN1, EPS15L14.666 × 10−52.053 × 10−3
 Endoplasmic reticulum tubular network2/12KPNB1, RAB185.296 × 10−40.0136
 Platelet alpha granule membrane2/13ITGB3, PECAM16.248 × 10−40.0136
 Cytosolic large ribosomal subunit3/67RPL4, RPL5, RPL179.556 × 10−40.0136
  1. aIn this dual evaluation, IMSGC GWAS was the discovery set and GeneMSA was the evaluation set
  2. bContributing genes: the number of genes in the input gene set. Term size: the total number of genes in the corresponding GO term
  3. cContributing genes: those in the input genes that contributed to the enrichment
  4. dAdjusted p-value by the Benjamini-Hochberg method [28]