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. 2019 May 9;10:1063. doi: 10.3389/fimmu.2019.01063

Table 4.

Ingenuity Pathway Analysis of differentially expressed genes from the fetal sheep microglia whole transcriptomes analysis.

Comparison # genes Top 10 signaling pathways -log(p-value)
LPS100 vs. Control 1779 Role of Macrophages, Fibroblasts and Endothelial Cells in Rheumatoid Arthritis 16.7
Dendritic Cell Maturation 12.9
iNOS Signaling 12.6
Role of IL-17A in Arthritis 12.5
IL-10 Signaling 11.8
Role of Tissue Factor in Cancer 11.6
Production of Nitric Oxide and Reactive Oxygen Species in Macrophages 11.1
Neuroinflammation Signaling Pathway 10.9
Toll-like Receptor Signaling 10.7
CD40 Signaling 10
LPS100+A10 vs. Control 4721 Molecular Mechanisms of Cancer 14.1
Colorectal Cancer Metastasis Signaling 11.2
Toll-like Receptor Signaling 11
NF-κB Signaling 10.6
Role of Macrophages, Fibroblasts and Endothelial Cells in Rheumatoid Arthritis 10.4
PI3K Signaling in B Lymphocytes 10.4
Role of Tissue Factor in Cancer 10.3
B Cell Receptor Signaling 9.83
TREM1 Signaling 7.83
Protein Kinase A Signaling 7.81
LPS100+B100 vs. Control 4049 Role of Macrophages, Fibroblasts and Endothelial Cells in Rheumatoid Arthritis 13.6
PI3K Signaling in B Lymphocytes 11.4
Production of Nitric Oxide and Reactive Oxygen Species in Macrophages 10.2
Molecular Mechanisms of Cancer 10.2
Activation of IRF by Cytosolic Pattern Recognition Receptors 10.2
IL-10 Signaling 9.63
B Cell Receptor Signaling 9.55
iNOS Signaling 9.21
Role of Tissue Factor in Cancer 9.06
Toll-like Receptor Signaling 8.93
LPS100+A10 vs. LPS100 8
LPS100+B100 vs. LPS100 0
LPS100+A10 vs. LPS100+B100 1132 T Cell Exhaustion Signaling Pathway 5.46
Dendritic Cell Maturation 5.43
Role of Macrophages, Fibroblasts and Endothelial Cells in Rheumatoid Arthritis 5.42
Altered T Cell and B Cell Signaling in Rheumatoid Arthritis 5.22
Th17 Activation Pathway 5.16
Leukocyte Extravasation Signaling 4.81
Superpathway of Cholesterol Biosynthesis 4.8
IL-10 Signaling 4.49
Role of Tissue Factor in Cancer 4.31
Th1 and Th2 Activation Pathway 4.26

Differential analysis of count data was done with the Bioconductor limma package. Differentially expressed genes were selected, based on a 1.5-fold change and an FDR < 0.05. Up regulation and down regulation represent positive and negative log2 fold changes, respectively. For details on “raw gene” level, see our GitHub repository or directly here. Bold font highlights signaling pathways common with astrocytes. Orange: positive z-score; blue: negative z-score. For further details as raw data and visualized activity patterns see GitHub.

Significant genes in microglia cultures at an FDR < 0.05 and a 1.5-fold change sorted on log(p-value).