Metascape Gene List Analysis Report
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Bar Graph Summary
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 2024-09-01). If multiple identifiers correspond to the same Entrez gene ID, they will be considered as a single Entrez gene ID in downstream analyses. The gene lists are summarized in Table 1.
Table 1. Statistics of input gene lists.
Name |
Total |
Unique |
MyList |
154 |
152 |
Gene Annotation
The following are the list of annotations retrieved from the latest version of the database (last updated on 2024-09-01) (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. |
Protein Functions (ChatGPT) |
Description |
Uncurated gene functions described by ChatGPT. |
Disease & Drugs (ChatGPT) |
Genotype/Phenotype/Disease |
Uncurated disease and drug associations described by ChatGPT. |
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, and WikiPathways. 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 distribution
2, and q-values are calculated using the Benjamini-Hochberg procedure to account for multiple testings
3. Kappa scores
4 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.
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.
GO |
Category |
Description |
Count |
% |
Log10(P) |
Log10(q) |
GO:0030036 |
GO Biological Processes |
actin cytoskeleton organization |
18 |
11.84 |
-9.41 |
-5.06 |
R-HSA-9012999 |
Reactome Gene Sets |
RHO GTPase cycle |
16 |
10.53 |
-8.96 |
-4.91 |
GO:0030865 |
GO Biological Processes |
cortical cytoskeleton organization |
6 |
3.95 |
-6.67 |
-3.23 |
GO:0051056 |
GO Biological Processes |
regulation of small GTPase mediated signal transduction |
11 |
7.24 |
-6.37 |
-3.03 |
GO:1990049 |
GO Biological Processes |
retrograde neuronal dense core vesicle transport |
3 |
1.97 |
-6.31 |
-3.02 |
GO:0030903 |
GO Biological Processes |
notochord development |
4 |
2.63 |
-5.65 |
-2.49 |
GO:0035239 |
GO Biological Processes |
tube morphogenesis |
14 |
9.21 |
-4.99 |
-1.95 |
GO:0031175 |
GO Biological Processes |
neuron projection development |
14 |
9.21 |
-4.95 |
-1.95 |
GO:0051493 |
GO Biological Processes |
regulation of cytoskeleton organization |
12 |
7.89 |
-4.85 |
-1.87 |
GO:0021782 |
GO Biological Processes |
glial cell development |
6 |
3.95 |
-4.33 |
-1.43 |
GO:0008285 |
GO Biological Processes |
negative regulation of cell population proliferation |
14 |
9.21 |
-4.33 |
-1.43 |
GO:0098657 |
GO Biological Processes |
import into cell |
13 |
8.55 |
-4.32 |
-1.43 |
GO:0001667 |
GO Biological Processes |
ameboidal-type cell migration |
7 |
4.61 |
-4.17 |
-1.31 |
GO:2000147 |
GO Biological Processes |
positive regulation of cell motility |
12 |
7.89 |
-4.12 |
-1.30 |
R-HSA-1483249 |
Reactome Gene Sets |
Inositol phosphate metabolism |
4 |
2.63 |
-3.93 |
-1.19 |
GO:0003333 |
GO Biological Processes |
amino acid transmembrane transport |
5 |
3.29 |
-3.88 |
-1.17 |
GO:0003158 |
GO Biological Processes |
endothelium development |
5 |
3.29 |
-3.78 |
-1.11 |
GO:0042982 |
GO Biological Processes |
amyloid precursor protein metabolic process |
3 |
1.97 |
-3.69 |
-1.07 |
GO:0048660 |
GO Biological Processes |
regulation of smooth muscle cell proliferation |
6 |
3.95 |
-3.61 |
-1.03 |
GO:1903076 |
GO Biological Processes |
regulation of protein localization to plasma membrane |
5 |
3.29 |
-3.61 |
-1.03 |
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
Cytoscape5, where each node represents an enriched term and is colored first by its cluster ID (Figure 2.a) and then by its p-value (Figure 2.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 2. 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.
Protein-protein Interaction Enrichment Analysis
For each given gene list, protein-protein interaction enrichment analysis has been carried out with the following databases: STRING
6, BioGrid
7, OmniPath
8, InWeb_IM
9.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) algorithm
10 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 3.
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 3.
Figure 3. Protein-protein interaction network and MCODE components identified in the gene lists.
 | |  |
| |
|
GO |
Description |
Log10(P) |
R-HSA-194315 |
Signaling by Rho GTPases |
-10.8 |
R-HSA-9716542 |
Signaling by Rho GTPases, Miro GTPases and RHOBTB3 |
-10.7 |
R-HSA-9012999 |
RHO GTPase cycle |
-10.4 |
| |
Color |
MCODE |
GO |
Description |
Log10(P) |
|
MCODE_2 |
GO:1990049 |
retrograde neuronal dense core vesicle transport |
-11.1 |
|
MCODE_2 |
GO:0030705 |
cytoskeleton-dependent intracellular transport |
-11.0 |
|
MCODE_2 |
GO:0047496 |
vesicle transport along microtubule |
-10.8 |
|
MCODE_3 |
R-HSA-9013106 |
RHOC GTPase cycle |
-13.1 |
|
MCODE_3 |
R-HSA-8980692 |
RHOA GTPase cycle |
-11.6 |
|
MCODE_3 |
R-HSA-9013026 |
RHOB GTPase cycle |
-9.9 |
|
Quality Control and Association Analysis
Gene list enrichments are identified in the following ontology categories: COVID, Cell_Type_Signatures, DisGeNET, PaGenBase, Transcription_Factor_Targets. 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 4-8. The algorithm used here is the same as that is used for pathway and process enrichment analysis.
Figure 4. Summary of enrichment analysis in COVID11.
|
|
GO |
Description |
Count |
% |
Log10(P) |
Log10(q) |
COVID018 |
RNA_Blanco-Melo_Lung_Up |
8 |
5.30 |
-8.00 |
-4.60 |
COVID059 |
Phosphoproteome_Bouhaddou_Vero_E6_24h_Down |
12 |
7.90 |
-7.40 |
-4.10 |
COVID065 |
Phosphoproteome_Bouhaddou_Vero_E6_8h_Down |
12 |
7.90 |
-7.40 |
-4.10 |
COVID243 |
RNA_Riva_Vero-E6_24h_Up |
11 |
7.20 |
-6.40 |
-3.30 |
COVID036 |
RNA_Sun_Calu-3_0h_Up |
10 |
6.60 |
-5.50 |
-2.40 |
COVID061 |
Phosphoproteome_Bouhaddou_Vero_E6_2h_Down |
10 |
6.60 |
-5.50 |
-2.40 |
COVID063 |
Phosphoproteome_Bouhaddou_Vero_E6_4h_Down |
8 |
5.30 |
-5.10 |
-2.10 |
COVID009 |
RNA_Blanco-Melo_A549-ACE2_Down |
8 |
5.30 |
-5.00 |
-2.00 |
COVID005 |
RNA_Appelberg_Huh-7_72h_Down |
9 |
5.90 |
-4.70 |
-1.80 |
COVID034 |
RNA_Liao_BALF-severe-vs-mild_Up |
9 |
5.90 |
-4.70 |
-1.80 |
COVID338 |
RNA_Wilk_B-cells_patient-C1B-severe_Down |
5 |
3.30 |
-4.40 |
-1.50 |
COVID007 |
RNA_Blanco-Melo_A549_Down |
8 |
5.30 |
-3.80 |
-1.20 |
COVID057 |
Phosphoproteome_Bouhaddou_Vero_E6_12h_Down |
8 |
5.30 |
-3.80 |
-1.20 |
COVID373 |
Interactome_Laurent_HEK293_24h_NSP2 |
7 |
4.60 |
-3.80 |
-1.20 |
COVID202 |
RNA_Vanderheiden_pHAE_48h_Down |
6 |
3.90 |
-3.40 |
-0.92 |
COVID055 |
Phosphoproteome_Bouhaddou_Vero_E6_0h_Down |
7 |
4.60 |
-3.30 |
-0.87 |
COVID023 |
RNA_Keller_B-cells-Infected_CD21pos_Down |
7 |
4.60 |
-3.30 |
-0.86 |
COVID058 |
Phosphoproteome_Bouhaddou_Vero_E6_12h_Up |
7 |
4.60 |
-3.10 |
-0.76 |
COVID062 |
Phosphoproteome_Bouhaddou_Vero_E6_2h_Up |
7 |
4.60 |
-3.10 |
-0.76 |
COVID234 |
Phosphoproteome_Klann_Caco-2_24h_Down |
7 |
4.60 |
-3.10 |
-0.76 |
|
Figure 5. Summary of enrichment analysis in Cell Type Signatures12.
|
|
GO |
Description |
Count |
% |
Log10(P) |
Log10(q) |
M39037 |
FAN EMBRYONIC CTX OLIG |
28 |
18.00 |
-16.00 |
-11.00 |
M39175 |
MURARO PANCREAS MESENCHYMAL STROMAL CELL |
26 |
17.00 |
-15.00 |
-11.00 |
M39050 |
MANNO MIDBRAIN NEUROTYPES HPERIC |
27 |
18.00 |
-14.00 |
-10.00 |
M39054 |
MANNO MIDBRAIN NEUROTYPES HRGL2B |
20 |
13.00 |
-13.00 |
-9.10 |
M39264 |
HU FETAL RETINA FIBROBLAST |
18 |
12.00 |
-12.00 |
-8.20 |
M39055 |
MANNO MIDBRAIN NEUROTYPES HRGL2A |
21 |
14.00 |
-11.00 |
-7.80 |
M40158 |
DESCARTES FETAL CEREBELLUM VASCULAR ENDOTHELIAL CELLS |
20 |
13.00 |
-10.00 |
-6.50 |
M39040 |
FAN EMBRYONIC CTX BRAIN ENDOTHELIAL 2 |
14 |
9.20 |
-9.30 |
-5.70 |
M39018 |
FAN EMBRYONIC CTX BIG GROUPS BRAIN ENDOTHELIAL |
14 |
9.20 |
-8.30 |
-4.70 |
M39167 |
GAO LARGE INTESTINE ADULT CJ IMMUNE CELLS |
16 |
11.00 |
-8.20 |
-4.70 |
M39128 |
AIZARANI LIVER C29 MVECS 2 |
13 |
8.60 |
-8.10 |
-4.70 |
M39279 |
DURANTE ADULT OLFACTORY NEUROEPITHELIUM VASCULAR SMOOTH MUSCLE CELLS |
8 |
5.30 |
-7.60 |
-4.20 |
M39056 |
MANNO MIDBRAIN NEUROTYPES HRGL3 |
16 |
11.00 |
-7.50 |
-4.10 |
M39039 |
FAN EMBRYONIC CTX BRAIN ENDOTHELIAL 1 |
14 |
9.20 |
-7.30 |
-4.00 |
M39053 |
MANNO MIDBRAIN NEUROTYPES HRGL2C |
12 |
7.90 |
-7.00 |
-3.70 |
M41666 |
TRAVAGLINI LUNG CAPILLARY INTERMEDIATE 1 CELL |
9 |
5.90 |
-7.00 |
-3.70 |
M40167 |
DESCARTES FETAL CEREBRUM VASCULAR ENDOTHELIAL CELLS |
15 |
9.90 |
-6.60 |
-3.30 |
M39176 |
MURARO PANCREAS ENDOTHELIAL CELL |
12 |
7.90 |
-6.50 |
-3.30 |
M41716 |
FAN OVARY CL14 MATURE SMOOTH MUSCLE CELL |
10 |
6.60 |
-5.40 |
-2.40 |
M39074 |
ZHONG PFC MAJOR TYPES ASTROCYTES |
10 |
6.60 |
-5.20 |
-2.20 |
|
Figure 6. Summary of enrichment analysis in DisGeNET13.
|
|
GO |
Description |
Count |
% |
Log10(P) |
Log10(q) |
C0278488 |
Carcinoma breast stage IV |
12 |
7.90 |
-4.50 |
-1.60 |
C0004158 |
Athetosis |
4 |
2.60 |
-4.40 |
-1.50 |
C0038525 |
Subarachnoid Hemorrhage |
11 |
7.20 |
-4.30 |
-1.50 |
C0280324 |
Laryngeal Squamous Cell Carcinoma |
11 |
7.20 |
-4.30 |
-1.50 |
C4551686 |
Malignant neoplasm of soft tissue |
13 |
8.60 |
-4.30 |
-1.50 |
C0027809 |
Neurilemmoma |
7 |
4.60 |
-4.30 |
-1.50 |
C1837279 |
Hypoplastic toenails |
4 |
2.60 |
-4.20 |
-1.50 |
C1858712 |
Spastic paraplegia 10, autosomal dominant |
3 |
2.00 |
-4.20 |
-1.40 |
C0555198 |
Malignant Glioma |
13 |
8.60 |
-4.10 |
-1.40 |
C2720436 |
Fibrosis of pleura |
3 |
2.00 |
-3.90 |
-1.20 |
C0020608 |
Hypodontia |
7 |
4.60 |
-3.90 |
-1.20 |
C0039101 |
synovial sarcoma |
8 |
5.30 |
-3.90 |
-1.20 |
C0015300 |
Exophthalmos |
7 |
4.60 |
-3.80 |
-1.20 |
C0025995 |
Micromelia |
5 |
3.30 |
-3.70 |
-1.10 |
C3642347 |
Basal-Like Breast Carcinoma |
7 |
4.60 |
-3.60 |
-1.00 |
C0264545 |
Thickening of pleura |
3 |
2.00 |
-3.60 |
-1.00 |
C0854917 |
Rhabdoid Tumor of the Kidney |
4 |
2.60 |
-3.60 |
-1.00 |
C0553580 |
Ewings sarcoma |
10 |
6.60 |
-3.50 |
-0.99 |
C0241181 |
Fragile skin |
3 |
2.00 |
-3.50 |
-0.99 |
C0685938 |
Malignant neoplasm of gastrointestinal tract |
9 |
5.90 |
-3.50 |
-0.99 |
|
Figure 7. Summary of enrichment analysis in PaGenBase14.
|
|
GO |
Description |
Count |
% |
Log10(P) |
Log10(q) |
PGB:00021 |
Tissue-specific: cortex |
4 |
2.60 |
-3.70 |
-1.10 |
PGB:00094 |
Cell-specific: Bronchial Epithelial Cells |
4 |
2.60 |
-2.30 |
-0.24 |
PGB:00032 |
Tissue-specific: Cerebellum |
4 |
2.60 |
-2.30 |
-0.21 |
|
Figure 8. Summary of enrichment analysis in Transcription Factor Targets.
|
|
GO |
Description |
Count |
% |
Log10(P) |
Log10(q) |
M19265 |
SREBP1 Q6 |
10 |
6.60 |
-6.30 |
-3.10 |
M2459 |
EGR Q6 |
10 |
6.60 |
-5.80 |
-2.70 |
M30192 |
TAZ TARGET GENES |
12 |
7.90 |
-5.20 |
-2.20 |
M17000 |
CP2 01 |
9 |
5.90 |
-5.20 |
-2.10 |
M13482 |
ZIC1 01 |
9 |
5.90 |
-5.10 |
-2.10 |
M1460 |
TGGNNNNNNKCCAR UNKNOWN |
11 |
7.20 |
-4.90 |
-1.90 |
M16022 |
CTAWWWATA RSRFC4 Q2 |
10 |
6.60 |
-4.80 |
-1.80 |
M551 |
TEF1 Q6 |
8 |
5.30 |
-4.70 |
-1.80 |
M4831 |
SP1 01 |
8 |
5.30 |
-4.50 |
-1.70 |
M15929 |
MEF2 Q6 01 |
8 |
5.30 |
-4.40 |
-1.50 |
M19851 |
FOXO3 01 |
8 |
5.30 |
-4.40 |
-1.50 |
M10112 |
RNGTGGGC UNKNOWN |
14 |
9.20 |
-4.40 |
-1.50 |
M2389 |
E47 02 |
8 |
5.30 |
-4.30 |
-1.50 |
M9300 |
SP1 Q4 01 |
8 |
5.30 |
-4.30 |
-1.50 |
M30410 |
ZSCAN5C TARGET GENES |
6 |
3.90 |
-4.00 |
-1.30 |
M11345 |
AP4 Q6 |
7 |
4.60 |
-3.80 |
-1.20 |
M11934 |
SRF Q5 01 |
7 |
4.60 |
-3.80 |
-1.20 |
M6568 |
TAAWWATAG RSRFC4 Q2 |
6 |
3.90 |
-3.60 |
-1.00 |
M9557 |
SP1 Q6 01 |
7 |
4.60 |
-3.60 |
-1.00 |
M5320 |
HIF1 Q5 |
7 |
4.60 |
-3.60 |
-1.00 |
|
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