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Table 4 Network and pathway analysis showing the most likely candidate genes with functional relevance in autoimmunity

From: Novel and rare functional genomic variants in multiple autoimmune syndrome and Sjögren’s syndrome

Gene Network algorithm (P value) Network node GeneGO ontology process Processes P value
LRP1 Analyse network (3.03e−7) PKC alpha (phosphorylation of the A2M receptor encoded by LRP1) (Figure 1) Phagocytosis 7.596e−8
LRP1 Analyse network (3.03e−7) PKC-alpha (phosphorylation of the A2M receptor encoded by LRP1) (Figure 1) Regulation of phospholipase A2 activity 3.597e−13
LRP1 Analyse network (3.03e−7) PKC-alpha (phosphorylation of the A2M receptor encoded by LRP1) (Figure 1) Negative regulation of apoptosis 6.703e−21
LRP1 Shortest paths (N/A) LRP1 (transcription regulation) IFN-gamma (Figure 2) Response to lipopolysaccharide 7.616e−21
MICAL1 Analyse network (7.32e−10) PKC-mu MICAL1 (Figure 3) Negative regulation of apoptotic process 7.901e−15
MICAL1 Analyse network (7.32e−10) PKC-mu MICAL1 (Figure 3) Actin filament depolymerisation 2.34e−2
MICAL1 Analyse network (7.32e−10) PKC-mu MICAL1 (Figure 3) Negative regulation of cysteine type endopeptidase activity 5.403e−3
  1. The first P value is of the constructed network. This gives the probability of obtaining a certain number of genes obtained from a given network algorithm from the input list by random chance. Also given are the network nodes and their corresponding biological processes that may have functional importance in ADs.