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PPI analysis workflow. A- PPI analysis of 337 SCZ risk genes (15) showed a significant connected network including 327 of these genes (p=0.03). (B) These 327 genes were further investigated using <t>GeneNets</t> and found to be connected in a network with significant mitochondrial genes from our study (n=19). C- 158 SCZ risk genes were connected with 14 mitochondrial genes in a significant network (p=0.02) (“mito-SCZ network”). D- Pathways and biological processes associated with the mito-SCZ network were investigated using GeNets and IPA software.
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PPI analysis workflow. A- PPI analysis of 337 SCZ risk genes (15) showed a significant connected network including 327 of these genes (p=0.03). (B) These 327 genes were further investigated using GeneNets and found to be connected in a network with significant mitochondrial genes from our study (n=19). C- 158 SCZ risk genes were connected with 14 mitochondrial genes in a significant network (p=0.02) (“mito-SCZ network”). D- Pathways and biological processes associated with the mito-SCZ network were investigated using GeNets and IPA software.

Journal: Biological psychiatry

Article Title: A comprehensive analysis of nuclear-encoded mitochondrial genes in schizophrenia

doi: 10.1016/j.biopsych.2018.02.1175

Figure Lengend Snippet: PPI analysis workflow. A- PPI analysis of 337 SCZ risk genes (15) showed a significant connected network including 327 of these genes (p=0.03). (B) These 327 genes were further investigated using GeneNets and found to be connected in a network with significant mitochondrial genes from our study (n=19). C- 158 SCZ risk genes were connected with 14 mitochondrial genes in a significant network (p=0.02) (“mito-SCZ network”). D- Pathways and biological processes associated with the mito-SCZ network were investigated using GeNets and IPA software.

Article Snippet: After constructing the network, we then used GeneNets toolbox in MATLAB (R2015a) ( 44 ) to determine whether the connectivity among the 327 ‘seed’ genes was statistically significant compared to a randomly selected network of similar size (taking into account number of genes and genes sizes).

Techniques: Software