Metascape Gene List Analysis Report

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Heatmap Summary

Figure 1. Heatmap of enriched terms across input gene lists, colored by p-values.
Metascape only visualizes the top 20 clusters. Up to 100 enriched clusters can be viewed here.
The top-level Gene Ontology biological processes can be viewed here.

The heatmap can be interactively viewed using JTreeView2 (.cdt, .gtr and .atr files can be found in the Zip package).

Gene Lists

User-provided gene identifiers are first converted into their corresponding H. sapiens Entrez gene IDs using the latest version of the database (last updated on 2023-01-01). If multiple identifiers correspond to the same Entrez gene ID, they will be considered as a single Entrez gene ID in downstream analyses. Each gene list is assigned a unique color, which is used throughout the analysis. The gene lists are summarized in Table 1.

Table 1. Statistics of input gene lists.
Name Total Unique Color Code
down DLE 331 331
down shHMOX1 48 48
up DLE 469 469
up shHMOX1 44 44
The overlaps between these lists are shown in a Circos3 plot (Figure 2.a). Another useful representation is to overlap genes based on their functions or shared pathways. The overlaps between gene lists can be significantly improved by considering overlaps between genes sharing the same enriched ontology term(s) (Figure 2.b). Only ontology terms that contain less than 100 genes are used to calculate functional overlaps to avoid linking genes using very general annotation. (We do not want to link all genes, only genes that belong to specific biological processes.)
Figure 2. Overlap between gene lists: (a) only at the gene level, where purple curves link identical genes; (b) including the shared term level, where blue curves link genes that belong to the same enriched ontology term. The inner circle represents gene lists, where hits are arranged along the arc. Genes that hit multiple lists are colored in dark orange, and genes unique to a list are shown in light orange. The publication-quality version of the figures is included in the Zip package as a .svg file under the Overlap_circos folder (readable by popular web browsers and Adobe Illustrator).

Gene Annotation

The following are the list of annotations retrieved from the latest version of the database (last updated on 2023-01-01) (Table 2).

Table 2. Gene annotations extracted
Name Type Description
Gene Symbol Description Primary HUGO gene symbol.
Description Description Short description.
Biological Process (GO) Function/Location Descriptions summarized based on gene ontology database, where up to three most informative GO terms are kept.
Kinase Class (UniProt) Function/Location Detailed kinase classes.
Protein Function (Protein Atlas) Function/Location Protein Function (Protein Atlas)
Subcellular Location (Protein Atlas) Function/Location Subcellular Location (Protein Atlas)
Drug (DrugBank) Genotype/Phenotype/Disease Drug information for the given gene as target.
Canonical Pathways Ontology Canonical Pathways
Hallmark Gene Sets Ontology Hallmark Gene Sets

Pathway and Process Enrichment Analysis

For each given gene list, pathway and process enrichment analysis have been carried out with the following ontology sources: KEGG Pathway, GO Biological Processes, Reactome Gene Sets, Canonical Pathways, CORUM, WikiPathways, and PANTHER Pathway. All genes in the genome have been used as the enrichment background. Terms with a p-value < 0.01, a minimum count of 3, and an enrichment factor > 1.5 (the enrichment factor is the ratio between the observed counts and the counts expected by chance) are collected and grouped into clusters based on their membership similarities. More specifically, p-values are calculated based on the cumulative hypergeometric distribution4, and q-values are calculated using the Benjamini-Hochberg procedure to account for multiple testings5. Kappa scores6 are used as the similarity metric when performing hierarchical clustering on the enriched terms, and sub-trees with a similarity of > 0.3 are considered a cluster. The most statistically significant term within a cluster is chosen to represent the cluster.

When multiple gene lists are provided, all lists are merged into one list called "_FINAL". A term may be found enriched in several individual gene lists and/or in the _FINAL gene list, and the best p-value among them is chosen as the final p-value. The pathway/process clusters that are found to be of interest (either shared or unique based on specific list enrichment) are used to prioritize the genes that fall into those clusters (membership is presented as 1/0 binary columns in the Excel spreadsheet). Note that individual gene lists containing more than 3000 genes are ignored during the enrichment analysis to avoid superficial terms; this is because long gene lists are often not random and generally trigger too many terms that are not of direct relevance to the biology under study.

Table 3. Top 20 clusters with their representative enriched terms (one per cluster). "Count" is the number of genes in the user-provided lists with membership in the given ontology term. "%" is the percentage of all of the user-provided genes that are found in the given ontology term (only input genes with at least one ontology term annotation are included in the calculation). "Log10(P)" is the p-value in log base 10. "Log10(q)" is the multi-test adjusted p-value in log base 10. __PATTERN__ shows the color code used for the gene lists where the term is found statistically significant, i.e., multiple colors indicate a pathway/process that is shared across multiple lists.
_PATTERN_ GO Category Description Count % Log10(P) Log10(q)
GO:0045087 GO Biological Processes innate immune response 108 23.33 -72.50 -68.15
GO:0050778 GO Biological Processes positive regulation of immune response 93 20.09 -63.78 -59.73
GO:0045321 GO Biological Processes leukocyte activation 83 17.93 -54.32 -50.58
GO:0031347 GO Biological Processes regulation of defense response 91 19.65 -52.83 -49.26
R-HSA-1280215 Reactome Gene Sets Cytokine Signaling in Immune system 83 17.93 -46.54 -43.27
GO:0002694 GO Biological Processes regulation of leukocyte activation 74 15.98 -43.92 -40.72
GO:0009617 GO Biological Processes response to bacterium 76 16.41 -41.22 -38.13
GO:0002683 GO Biological Processes negative regulation of immune system process 60 12.96 -35.35 -32.40
GO:0006954 GO Biological Processes inflammatory response 61 13.17 -33.72 -30.78
R-HSA-1280218 Reactome Gene Sets Adaptive Immune System 71 15.33 -33.67 -30.75
GO:0071345 GO Biological Processes cellular response to cytokine stimulus 66 14.25 -31.09 -28.28
GO:0002697 GO Biological Processes regulation of immune effector process 48 10.37 -28.53 -25.79
GO:0002252 GO Biological Processes immune effector process 46 9.94 -26.29 -23.61
WP5115 WikiPathways Network map of SARS-CoV-2 signaling pathway 36 7.78 -25.72 -23.05
WP5218 WikiPathways Extrafollicular and follicular B cell activation by SARS-CoV-2 24 5.18 -24.70 -22.07
GO:0008544 GO Biological Processes epidermis development 34 10.59 -23.02 -20.46
R-HSA-6798695 Reactome Gene Sets Neutrophil degranulation 45 9.72 -21.45 -18.93
WP619 WikiPathways Type II interferon signaling 16 3.46 -19.16 -16.71
GO:0002688 GO Biological Processes regulation of leukocyte chemotaxis 24 5.18 -18.82 -16.42
GO:0050727 GO Biological Processes regulation of inflammatory response 38 8.21 -17.91 -15.54

To further capture the relationships between the terms, a subset of enriched terms has been selected and rendered as a network plot, where terms with a similarity > 0.3 are connected by edges. We select the terms with the best p-values from each of the 20 clusters, with the constraint that there are no more than 15 terms per cluster and no more than 250 terms in total. The network is visualized using Cytoscape7, where each node represents an enriched term and is colored first by its cluster ID (Figure 3.a) and then by its p-value (Figure 3.b). These networks can be interactively viewed in Cytoscape through the .cys files (contained in the Zip package, which also contains a publication-quality version as a PDF) or within a browser by clicking on the web icon. For clarity, term labels are only shown for one term per cluster, so it is recommended to use Cytoscape or a browser to visualize the network in order to inspect all node labels. We can also export the network into a PDF file within Cytoscape, and then edit the labels using Adobe Illustrator for publication purposes. To switch off all labels, delete the "Label" mapping under the "Style" tab within Cytoscape, and then export the network view.

Figure 3. Network of enriched terms: (a) colored by cluster ID, where nodes that share the same cluster ID are typically close to each other; (b) colored by p-value, where terms containing more genes tend to have a more significant p-value.

In the case of when multiple gene lists are provided, the nodes are represented as pie charts, where the size of a pie is proportional to the total number of hits that fall into that specific term. The pie charts are color-coded based on the gene list identities, where the size of a slice represents the percentage of genes under the term that originated from the corresponding gene list. This plot is particularly useful for visualizing whether the terms are shared by multiple lists or unique to a specific list, as well as for understanding how these terms associate with each other within the biological context of the meta study (Figure 4).

Figure 4. Network of enriched terms represented as pie charts, where pies are color-coded based on the identities of the gene lists.

Protein-protein Interaction Enrichment Analysis

For each given gene list, protein-protein interaction enrichment analysis has been carried out with the following databases: STRING8, BioGrid9, OmniPath10, InWeb_IM11.Only physical interactions in STRING (physical score > 0.132) and BioGrid are used (details). The resultant network contains the subset of proteins that form physical interactions with at least one other member in the list. If the network contains between 3 and 500 proteins, the Molecular Complex Detection (MCODE) algorithm12 has been applied to identify densely connected network components. The MCODE networks identified for individual gene lists have been gathered and are shown in Figure 5.

Pathway and process enrichment analysis has been applied to each MCODE component independently, and the three best-scoring terms by p-value have been retained as the functional description of the corresponding components, shown in the tables underneath corresponding network plots within Figure 5.

Figure 5. Protein-protein interaction network and MCODE components identified in the gene lists.

down DLE (Full Connection)

GO Description Log10(P)
GO:0008544 epidermis development -19.9
GO:0043588 skin development -17.2
GO:0030855 epithelial cell differentiation -12.1

down DLE (Keep MCODE Nodes Only)

Color MCODE GO Description Log10(P)
MCODE_1 GO:0045109 intermediate filament organization -9.0
MCODE_1 GO:0031424 keratinization -8.8
MCODE_1 GO:0045104 intermediate filament cytoskeleton organization -8.6
MCODE_2 R-HSA-6798695 Neutrophil degranulation -6.0
MCODE_2 R-HSA-6809371 Formation of the cornified envelope -5.8
MCODE_2 GO:0045216 cell-cell junction organization -5.4
MCODE_3 GO:0002181 cytoplasmic translation -14.4
MCODE_3 CORUM:306 Ribosome, cytoplasmic -12.2
MCODE_3 WP477 Cytoplasmic ribosomal proteins -11.9
MCODE_4 hsa04710 Circadian rhythm -11.2
MCODE_4 GO:0048511 rhythmic process -10.2
MCODE_4 GO:0032922 circadian regulation of gene expression -9.9
MCODE_5 R-HSA-73980 RNA Polymerase III Transcription Termination -11.9
MCODE_5 R-HSA-74158 RNA Polymerase III Transcription -10.8
MCODE_5 R-HSA-749476 RNA Polymerase III Abortive And Retractive Initiation -10.8
MCODE_8 R-HSA-381676 Glucagon-like Peptide-1 (GLP1) regulates insulin secretion -8.6
MCODE_8 R-HSA-4086398 Ca2+ pathway -8.1
MCODE_8 R-HSA-422356 Regulation of insulin secretion -7.8
MCODE_9 R-HSA-6807878 COPI-mediated anterograde transport -7.4
MCODE_9 R-HSA-199977 ER to Golgi Anterograde Transport -6.9
MCODE_9 R-HSA-948021 Transport to the Golgi and subsequent modification -6.6
MCODE_10 GO:0048706 embryonic skeletal system development -7.1
MCODE_10 GO:0009952 anterior/posterior pattern specification -6.5
MCODE_10 GO:0003002 regionalization -5.6

down shHMOX1 (Full Connection)

GO Description Log10(P)
WP2814 Mammary gland development pathway - Puberty (Stage 2 of 4) -7.0
R-HSA-6785807 Interleukin-4 and Interleukin-13 signaling -6.0
R-HSA-109582 Hemostasis -5.4

up DLE (Full Connection)

GO Description Log10(P)
GO:0045087 innate immune response -80.4
GO:0050778 positive regulation of immune response -66.7
GO:0045321 leukocyte activation -57.2

up DLE (Keep MCODE Nodes Only)

Color MCODE GO Description Log10(P)
MCODE_1 R-HSA-909733 Interferon alpha/beta signaling -59.2
MCODE_1 R-HSA-913531 Interferon Signaling -48.4
MCODE_1 GO:0051607 defense response to virus -39.5
MCODE_2 R-HSA-375276 Peptide ligand-binding receptors -38.2
MCODE_2 R-HSA-373076 Class A/1 (Rhodopsin-like receptors) -37.3
MCODE_2 R-HSA-500792 GPCR ligand binding -34.5
MCODE_3 hsa04613 Neutrophil extracellular trap formation -9.0
MCODE_3 R-HSA-3214815 HDACs deacetylate histones -8.7
MCODE_3 R-HSA-6799990 Metal sequestration by antimicrobial proteins -8.4
MCODE_4 R-HSA-202427 Phosphorylation of CD3 and TCR zeta chains -18.1
MCODE_4 M34 PID TCR PATHWAY -17.2
MCODE_4 M124 PID CXCR4 PATHWAY -15.6
MCODE_5 R-HSA-388841 Costimulation by the CD28 family -17.1
MCODE_5 GO:0031295 T cell costimulation -15.4
MCODE_5 GO:0031294 lymphocyte costimulation -15.3
MCODE_6 CORUM:6418 C1q complex -10.9
MCODE_6 R-HSA-166663 Initial triggering of complement -10.7
MCODE_6 WP545 Complement activation -10.7
MCODE_7 R-HSA-6809371 Formation of the cornified envelope -11.9
MCODE_7 R-HSA-6805567 Keratinization -10.8
MCODE_7 GO:0031424 keratinization -9.6
MCODE_8 GO:0007204 positive regulation of cytosolic calcium ion concentration -9.0
MCODE_8 R-HSA-416476 G alpha (q) signalling events -8.6
MCODE_8 GO:0051482 positive regulation of cytosolic calcium ion concentration involved in phospholipase C-activating G protein-coupled signaling pathway -8.4
MCODE_9 R-HSA-1679131 Trafficking and processing of endosomal TLR -10.2
MCODE_9 GO:0019886 antigen processing and presentation of exogenous peptide antigen via MHC class II -9.0
MCODE_9 GO:0002495 antigen processing and presentation of peptide antigen via MHC class II -8.9

up shHMOX1 (Full Connection)

GO Description Log10(P)
M256 PID TAP63 PATHWAY -4.8
R-HSA-68886 M Phase -4.5
R-HSA-2262752 Cellular responses to stress -4.2

up shHMOX1 (Keep MCODE Nodes Only)

Color MCODE GO Description Log10(P)
MCODE_1 R-HSA-9609690 HCMV Early Events -5.3
MCODE_1 R-HSA-9609646 HCMV Infection -5.1
MCODE_1 GO:1903311 regulation of mRNA metabolic process -4.2

All lists merged Colored by Counts(Full Connection)

GO Description Log10(P)
GO:0045087 innate immune response -75.5
GO:0050778 positive regulation of immune response -62.8
GO:0001775 cell activation -59.6

All lists merged Colored by Counts(Keep MCODE Nodes Only)

Color MCODE GO Description Log10(P)
MCODE_1 GO:0045109 intermediate filament organization -12.8
MCODE_1 GO:0031424 keratinization -12.4
MCODE_1 GO:0045104 intermediate filament cytoskeleton organization -12.1
MCODE_2 R-HSA-909733 Interferon alpha/beta signaling -59.2
MCODE_2 R-HSA-913531 Interferon Signaling -48.4
MCODE_2 GO:0051607 defense response to virus -39.5
MCODE_3 R-HSA-418594 G alpha (i) signalling events -37.8
MCODE_3 R-HSA-373076 Class A/1 (Rhodopsin-like receptors) -37.3
MCODE_3 R-HSA-375276 Peptide ligand-binding receptors -35.1
MCODE_4 hsa04710 Circadian rhythm -11.1
MCODE_4 M95 PID CIRCADIAN PATHWAY -9.9
MCODE_4 GO:0032922 circadian regulation of gene expression -9.4
MCODE_5 R-HSA-388841 Costimulation by the CD28 family -28.9
MCODE_5 M34 PID TCR PATHWAY -26.2
MCODE_5 GO:0050778 positive regulation of immune response -21.7
MCODE_6 R-HSA-1679131 Trafficking and processing of endosomal TLR -7.9
MCODE_6 M5885 NABA MATRISOME ASSOCIATED -6.7
MCODE_6 GO:0019886 antigen processing and presentation of exogenous peptide antigen via MHC class II -6.7
MCODE_7 R-HSA-6799990 Metal sequestration by antimicrobial proteins -9.4
MCODE_7 GO:0035425 autocrine signaling -9.2
MCODE_7 GO:0052548 regulation of endopeptidase activity -7.7
MCODE_8 R-HSA-6809371 Formation of the cornified envelope -19.0
MCODE_8 R-HSA-6805567 Keratinization -17.2
MCODE_8 GO:0031424 keratinization -17.2
MCODE_9 hsa04024 cAMP signaling pathway -7.4
MCODE_9 hsa04371 Apelin signaling pathway -5.7
MCODE_9 R-HSA-9006925 Intracellular signaling by second messengers -4.7
MCODE_10 R-HSA-166663 Initial triggering of complement -12.6
MCODE_10 WP545 Complement activation -12.6
MCODE_10 GO:0006958 complement activation, classical pathway -12.1
MCODE_11 GO:0007204 positive regulation of cytosolic calcium ion concentration -9.0
MCODE_11 R-HSA-416476 G alpha (q) signalling events -8.6
MCODE_11 GO:0051482 positive regulation of cytosolic calcium ion concentration involved in phospholipase C-activating G protein-coupled signaling pathway -8.4
MCODE_12 GO:0048245 eosinophil chemotaxis -9.2
MCODE_12 GO:0072677 eosinophil migration -9.1
MCODE_12 GO:0002548 monocyte chemotaxis -8.5
MCODE_15 hsa04650 Natural killer cell mediated cytotoxicity -7.1
MCODE_15 R-HSA-198933 Immunoregulatory interactions between a Lymphoid and a non-Lymphoid cell -7.1
MCODE_15 R-HSA-1280218 Adaptive Immune System -4.8
MCODE_16 R-HSA-195258 RHO GTPase Effectors -5.9
MCODE_16 GO:0030036 actin cytoskeleton organization -5.3
MCODE_16 GO:0097435 supramolecular fiber organization -5.2
MCODE_17 GO:0009611 response to wounding -5.5
MCODE_17 R-HSA-109582 Hemostasis -5.1

All lists merged Colored by Cluster(Full Connection)

GO Description Log10(P)
GO:0045087 innate immune response -75.5
GO:0050778 positive regulation of immune response -62.8
GO:0001775 cell activation -59.6

All lists merged Colored by Cluster(Keep MCODE Nodes Only)

Color MCODE GO Description Log10(P)
MCODE_1 GO:0045109 intermediate filament organization -12.8
MCODE_1 GO:0031424 keratinization -12.4
MCODE_1 GO:0045104 intermediate filament cytoskeleton organization -12.1
MCODE_2 R-HSA-909733 Interferon alpha/beta signaling -59.2
MCODE_2 R-HSA-913531 Interferon Signaling -48.4
MCODE_2 GO:0051607 defense response to virus -39.5
MCODE_3 R-HSA-418594 G alpha (i) signalling events -37.8
MCODE_3 R-HSA-373076 Class A/1 (Rhodopsin-like receptors) -37.3
MCODE_3 R-HSA-375276 Peptide ligand-binding receptors -35.1
MCODE_4 hsa04710 Circadian rhythm -11.1
MCODE_4 M95 PID CIRCADIAN PATHWAY -9.9
MCODE_4 GO:0032922 circadian regulation of gene expression -9.4
MCODE_5 R-HSA-388841 Costimulation by the CD28 family -28.9
MCODE_5 M34 PID TCR PATHWAY -26.2
MCODE_5 GO:0050778 positive regulation of immune response -21.7
MCODE_6 R-HSA-1679131 Trafficking and processing of endosomal TLR -7.9
MCODE_6 M5885 NABA MATRISOME ASSOCIATED -6.7
MCODE_6 GO:0019886 antigen processing and presentation of exogenous peptide antigen via MHC class II -6.7
MCODE_7 R-HSA-6799990 Metal sequestration by antimicrobial proteins -9.4
MCODE_7 GO:0035425 autocrine signaling -9.2
MCODE_7 GO:0052548 regulation of endopeptidase activity -7.7
MCODE_8 R-HSA-6809371 Formation of the cornified envelope -19.0
MCODE_8 R-HSA-6805567 Keratinization -17.2
MCODE_8 GO:0031424 keratinization -17.2
MCODE_9 hsa04024 cAMP signaling pathway -7.4
MCODE_9 hsa04371 Apelin signaling pathway -5.7
MCODE_9 R-HSA-9006925 Intracellular signaling by second messengers -4.7
MCODE_10 R-HSA-166663 Initial triggering of complement -12.6
MCODE_10 WP545 Complement activation -12.6
MCODE_10 GO:0006958 complement activation, classical pathway -12.1
MCODE_11 GO:0007204 positive regulation of cytosolic calcium ion concentration -9.0
MCODE_11 R-HSA-416476 G alpha (q) signalling events -8.6
MCODE_11 GO:0051482 positive regulation of cytosolic calcium ion concentration involved in phospholipase C-activating G protein-coupled signaling pathway -8.4
MCODE_12 GO:0048245 eosinophil chemotaxis -9.2
MCODE_12 GO:0072677 eosinophil migration -9.1
MCODE_12 GO:0002548 monocyte chemotaxis -8.5
MCODE_15 hsa04650 Natural killer cell mediated cytotoxicity -7.1
MCODE_15 R-HSA-198933 Immunoregulatory interactions between a Lymphoid and a non-Lymphoid cell -7.1
MCODE_15 R-HSA-1280218 Adaptive Immune System -4.8
MCODE_16 R-HSA-195258 RHO GTPase Effectors -5.9
MCODE_16 GO:0030036 actin cytoskeleton organization -5.3
MCODE_16 GO:0097435 supramolecular fiber organization -5.2
MCODE_17 GO:0009611 response to wounding -5.5
MCODE_17 R-HSA-109582 Hemostasis -5.1

Quality Control and Association Analysis

Gene list enrichments are identified in the following ontology categories: COVID, TRRUST, Transcription_Factor_Targets, Cell_Type_Signatures, DisGeNET, PaGenBase. All genes in the genome have been used as the enrichment background. Terms with a p-value < 0.01, a minimum count of 3, and an enrichment factor > 1.5 (the enrichment factor is the ratio between the observed counts and the counts expected by chance) are collected and grouped into clusters based on their membership similarities. The top few enriched clusters (one term per cluster) are shown in the Figure 6-11. The algorithm used here is the same as that is used for pathway and process enrichment analysis.

Figure 6. Summary of enrichment analysis in COVID13.


_PATTERN_ GO Description Count % Log10(P) Log10(q)
COVID011 RNA_Blanco-Melo_A549-ACE2-ruxolitinib_Down 89 19.00 -100.00 -96.00
COVID017 RNA_Blanco-Melo_Lung_Down 96 21.00 -100.00 -96.00
COVID353 RNA_Zhang_Monocytes_severe-and-moderate_Up 75 16.00 -100.00 -96.00
COVID050 RNA_Wyler_Calu-3_24h_Up 93 20.00 -95.00 -91.00
COVID048 RNA_Wyler_Calu-3_12h_Up 85 18.00 -83.00 -79.00
COVID016 RNA_Blanco-Melo_Calu-3_Up 84 18.00 -81.00 -78.00
COVID359 RNA_Zhang_T-cells_severe-and-moderate_Up 63 14.00 -76.00 -73.00
COVID356 RNA_Zhang_NK-cells_severe-and-moderate_Up 53 11.00 -70.00 -67.00
COVID241 RNA_Lieberman_Nasopharynx_High_vs_Low_Up 64 14.00 -70.00 -67.00
COVID244 RNA_Wilk_CD14+Monocytes_patient-C1A-mild_Up 46 9.90 -62.00 -59.00
COVID297 RNA_Wilk_NK-cells_patient-C5_Up 39 8.40 -60.00 -57.00
COVID362 RNA_Zhang_B-cells_severe-and-moderate_Up 43 9.30 -58.00 -55.00
COVID239 RNA_Lieberman_Nasopharynx_Infected_vs_Neg_Up 35 7.60 -57.00 -54.00
COVID256 RNA_Wilk_CD14+Monocytes_patient-C6_Up 53 11.00 -56.00 -53.00
COVID254 RNA_Wilk_CD14+Monocytes_patient-C5_Up 46 9.90 -55.00 -52.00
COVID266 RNA_Wilk_CD16+Monocytes_patient-C4_Up 41 8.90 -53.00 -50.00
COVID252 RNA_Wilk_CD14+Monocytes_patient-C4_Up 41 8.90 -53.00 -50.00
COVID038 RNA_Sun_Calu-3_12h_Up 63 14.00 -52.00 -49.00
COVID329 RNA_Wilk_CD4+T-cells_patient-C5_Up 31 6.70 -50.00 -47.00
COVID282 RNA_Wilk_Dendritic-cells_patient-C5_Up 38 8.20 -49.00 -46.00
Figure 7. Summary of enrichment analysis in TRRUST.


_PATTERN_ GO Description Count % Log10(P) Log10(q)
TRR00875 Regulated by: NFKB1 40 8.60 -23.00 -21.00
TRR01158 Regulated by: RELA 39 8.40 -22.00 -20.00
TRR01275 Regulated by: STAT1 19 4.10 -15.00 -13.00
TRR01264 Regulated by: SPI1 16 3.50 -15.00 -13.00
TRR00602 Regulated by: IRF1 13 2.80 -12.00 -9.90
TRR01256 Regulated by: SP1 28 6.00 -7.80 -6.10
TRR01424 Regulated by: TRERF1 5 1.10 -7.80 -6.00
TRR00645 Regulated by: JUN 15 3.20 -7.20 -5.40
TRR00016 Regulated by: ARNTL 4 1.20 -6.70 -5.00
TRR00129 Regulated by: CREB5 5 1.10 -6.00 -4.40
TRR00109 Regulated by: CEBPA 8 1.70 -5.50 -3.90
TRR00270 Regulated by: EP300 8 1.70 -5.30 -3.80
TRR00892 Regulated by: NPAS2 3 0.93 -5.30 -3.80
TRR01277 Regulated by: STAT3 12 2.60 -5.10 -3.60
TRR01276 Regulated by: STAT2 4 0.86 -4.60 -3.10
TRR00011 Regulated by: AR 4 8.30 -4.60 -3.10
TRR00119 Regulated by: CLOCK 4 1.20 -4.60 -3.10
TRR01157 Regulated by: REL 5 1.10 -4.40 -2.90
TRR00604 Regulated by: IRF3 4 0.86 -4.20 -2.80
TRR01419 Regulated by: TP53 4 9.10 -3.90 -2.50
Figure 8. Summary of enrichment analysis in Transcription Factor Targets14.


_PATTERN_ GO Description Count % Log10(P) Log10(q)
M16200 ISRE 01 31 6.70 -18.00 -16.00
M2727 ICSBP Q6 27 5.80 -14.00 -12.00
M533 STTTCRNTTT IRF Q6 23 5.00 -13.00 -11.00
M30054 MAML1 TARGET GENES 27 5.80 -12.00 -10.00
M14066 IRF Q6 24 5.20 -12.00 -10.00
M15616 RGAGGAARY PU1 Q6 34 7.30 -12.00 -9.90
M9412 RTTTNNNYTGGM UNKNOWN 16 5.00 -11.00 -9.00
M2709 IRF1 01 23 5.00 -11.00 -8.90
M12520 SOX9 B1 19 5.90 -11.00 -8.90
M30200 TERF1 TARGET GENES 24 5.20 -10.00 -8.50
M9902 ELF1 Q6 21 4.50 -9.50 -7.60
M12258 IRF7 01 21 4.50 -9.20 -7.30
M4770 COREBINDINGFACTOR Q6 21 4.50 -8.60 -6.80
M18230 ETS Q4 19 4.10 -7.80 -6.00
M572 TGCCAAR NF1 Q6 27 8.40 -7.60 -5.90
M14376 PU1 Q6 18 3.90 -7.50 -5.80
M9034 OCT1 04 15 4.70 -7.20 -5.50
M19265 SREBP1 Q6 15 4.70 -7.10 -5.40
M17687 IRF2 01 13 2.80 -7.00 -5.30
M3147 PAX4 03 15 4.70 -6.90 -5.20
Figure 9. Summary of enrichment analysis in Cell Type Signatures.


_PATTERN_ GO Description Count % Log10(P) Log10(q)
M39160 GAO LARGE INTESTINE 24W C11 PANETH LIKE CELL 103 22.00 -100.00 -96.00
M39305 CUI DEVELOPING HEART C8 MACROPHAGE 94 20.00 -100.00 -96.00
M40157 DESCARTES FETAL CEREBELLUM MICROGLIA 129 28.00 -100.00 -96.00
M39051 MANNO MIDBRAIN NEUROTYPES HMGL 114 25.00 -93.00 -89.00
M39266 HU FETAL RETINA MICROGLIA 94 20.00 -85.00 -82.00
M39166 GAO LARGE INTESTINE ADULT CI MESENCHYMAL CELLS 92 20.00 -85.00 -81.00
M39306 CUI DEVELOPING HEART C9 B T CELL 68 15.00 -81.00 -78.00
M39077 ZHONG PFC MAJOR TYPES MICROGLIA 95 21.00 -80.00 -77.00
M39022 FAN EMBRYONIC CTX BIG GROUPS MICROGLIA 89 19.00 -79.00 -76.00
M40210 DESCARTES FETAL INTESTINE MYELOID CELLS 71 15.00 -72.00 -69.00
M40168 DESCARTES FETAL CEREBRUM MICROGLIA 93 20.00 -72.00 -69.00
M39110 AIZARANI LIVER C6 KUPFFER CELLS 2 66 14.00 -64.00 -61.00
M39106 AIZARANI LIVER C2 KUPFFER CELLS 1 63 14.00 -64.00 -61.00
M39109 AIZARANI LIVER C5 NK NKT CELLS 3 54 12.00 -64.00 -60.00
M39105 AIZARANI LIVER C1 NK NKT CELLS 1 56 12.00 -60.00 -57.00
M40314 DESCARTES FETAL THYMUS ANTIGEN PRESENTING CELLS 57 12.00 -59.00 -56.00
M40264 DESCARTES FETAL PANCREAS MYELOID CELLS 63 14.00 -59.00 -56.00
M40154 DESCARTES FETAL ADRENAL LYMPHOID CELLS 55 12.00 -58.00 -55.00
M39021 FAN EMBRYONIC CTX BIG GROUPS BRAIN IMMUNE 53 11.00 -57.00 -54.00
M41715 FAN OVARY CL13 MONOCYTE MACROPHAGE 77 17.00 -56.00 -53.00
Figure 10. Summary of enrichment analysis in DisGeNET15.


_PATTERN_ GO Description Count % Log10(P) Log10(q)
C3714514 Infection 71 15.00 -47.00 -44.00
C0024138 Lupus Erythematosus, Discoid 72 16.00 -44.00 -42.00
C0024131 Lupus Vulgaris 67 14.00 -40.00 -38.00
C0004623 Bacterial Infections 71 15.00 -40.00 -37.00
C0409974 Lupus Erythematosus 68 15.00 -40.00 -37.00
C0018133 Graft-vs-Host Disease 60 13.00 -38.00 -35.00
C2363741 HIV-1 infection 72 16.00 -37.00 -35.00
C0524910 Hepatitis C, Chronic 55 12.00 -33.00 -31.00
C0036202 Sarcoidosis 53 11.00 -32.00 -30.00
C0524909 Hepatitis B, Chronic 53 11.00 -32.00 -29.00
C4048329 Immunosuppression 63 14.00 -32.00 -29.00
C0007570 Celiac Disease 58 13.00 -31.00 -29.00
C0021368 Inflammation 55 12.00 -31.00 -29.00
C0867389 Chronic graft-versus-host disease 42 9.10 -31.00 -28.00
C0011633 Dermatomyositis 41 8.90 -30.00 -28.00
C0011615 Dermatitis, Atopic 66 14.00 -30.00 -27.00
C0017661 IGA Glomerulonephritis 53 11.00 -30.00 -27.00
C0024143 Lupus Nephritis 55 12.00 -30.00 -27.00
C0042384 Vasculitis 44 9.50 -30.00 -27.00
C0019348 Herpes Simplex Infections 61 13.00 -29.00 -27.00
Figure 11. Summary of enrichment analysis in PaGenBase16.


_PATTERN_ GO Description Count % Log10(P) Log10(q)
PGB:00011 Tissue-specific: spleen 103 22.00 -85.00 -82.00
PGB:00041 Tissue-specific: Blood 69 15.00 -67.00 -64.00
PGB:00016 Tissue-specific: thymus 41 8.90 -32.00 -30.00
PGB:00017 Tissue-specific: skin 30 9.30 -24.00 -22.00
PGB:00048 Tissue-specific: bone marrow 34 7.30 -23.00 -21.00
PGB:00086 Cell-specific: Lymphoma burkitts Daudi 13 2.80 -13.00 -11.00
PGB:00081 Cell-specific: Bronchial Epithelial Cells 14 4.40 -9.60 -7.70
PGB:00018 Tissue-specific: lung 29 6.30 -8.90 -7.10
PGB:00125 Cell-specific: RS11846 6 1.30 -7.70 -6.00
PGB:00005 Tissue-specific: tonsil 10 2.20 -7.60 -5.90
PGB:00064 Cell-specific: RPMI 8226 8 1.70 -7.50 -5.80
PGB:00131 Cell-specific: B-lymphocyte 8 1.70 -6.40 -4.80
PGB:00043 Cell-specific: CD56+ NKCells 9 1.90 -6.20 -4.60
PGB:00156 Tissue-specific: Tongue 7 1.50 -6.10 -4.40
PGB:00036 Cell-specific: MOLT4 12 2.60 -5.80 -4.20
PGB:00053 Cell-specific: NHEK 20 4.30 -5.70 -4.10
PGB:00085 Cell-specific: RL7 6 1.30 -5.40 -3.90
PGB:00184 Cell-specific: SR 6 1.30 -5.00 -3.50
PGB:00082 Cell-specific: Breast cell 6 1.90 -4.60 -3.10
PGB:00010 Tissue-specific: adipose tissue 9 2.80 -4.00 -2.60

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