Metascape Gene List Analysis Report
metascape.org1
Heatmap Summary
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 |
NEGATIVELY |
50 |
48 |
|
POSITIVELY |
221 |
221 |
|
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 distribution
4, and q-values are calculated using the Benjamini-Hochberg procedure to account for multiple testings
5. Kappa scores
6 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) |
|
R-HSA-6798695 |
Reactome Gene Sets |
Neutrophil degranulation |
25 |
11.31 |
-13.63 |
-9.28 |
|
R-HSA-6809371 |
Reactome Gene Sets |
Formation of the cornified envelope |
12 |
5.43 |
-9.62 |
-5.66 |
|
R-HSA-194315 |
Reactome Gene Sets |
Signaling by Rho GTPases |
23 |
10.41 |
-8.54 |
-5.01 |
|
R-HSA-9711123 |
Reactome Gene Sets |
Cellular response to chemical stress |
13 |
5.88 |
-8.52 |
-5.01 |
|
R-HSA-2262752 |
Reactome Gene Sets |
Cellular responses to stress |
24 |
10.86 |
-8.33 |
-4.93 |
|
R-HSA-199991 |
Reactome Gene Sets |
Membrane Trafficking |
21 |
9.50 |
-7.97 |
-4.63 |
|
R-HSA-3700989 |
Reactome Gene Sets |
Transcriptional Regulation by TP53 |
16 |
7.24 |
-7.90 |
-4.59 |
|
R-HSA-9007101 |
Reactome Gene Sets |
Rab regulation of trafficking |
10 |
4.52 |
-7.55 |
-4.33 |
|
WP3888 |
WikiPathways |
VEGFA-VEGFR2 signaling pathway |
16 |
7.24 |
-6.84 |
-3.72 |
|
GO:0010506 |
GO Biological Processes |
regulation of autophagy |
14 |
6.33 |
-6.48 |
-3.39 |
|
CORUM:6182 |
CORUM |
PP2A A/C-striatin complex |
3 |
1.36 |
-6.41 |
-3.34 |
|
GO:0042176 |
GO Biological Processes |
regulation of protein catabolic process |
14 |
6.33 |
-6.29 |
-3.24 |
|
R-HSA-556833 |
Reactome Gene Sets |
Metabolism of lipids |
22 |
8.30 |
-6.09 |
-3.02 |
|
WP4856 |
WikiPathways |
Intracellular trafficking proteins involved in CMT neuropathy |
5 |
2.26 |
-5.85 |
-2.84 |
|
CORUM:938 |
CORUM |
FACT complex, UV-activated |
3 |
1.36 |
-5.42 |
-2.50 |
|
R-HSA-1640170 |
Reactome Gene Sets |
Cell Cycle |
18 |
8.14 |
-5.40 |
-2.50 |
|
GO:0006886 |
GO Biological Processes |
intracellular protein transport |
18 |
8.14 |
-5.37 |
-2.49 |
|
hsa04141 |
KEGG Pathway |
Protein processing in endoplasmic reticulum |
9 |
4.07 |
-5.29 |
-2.45 |
|
M186 |
Canonical Pathways |
PID PDGFRB PATHWAY |
8 |
3.62 |
-5.28 |
-2.45 |
|
CORUM:924 |
CORUM |
Toposome |
3 |
1.36 |
-4.88 |
-2.13 |
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: STRING
8, BioGrid
9, OmniPath
10, InWeb_IM
11.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
12 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.
 |
|
NEGATIVELY (Full Connection)
GO |
Description |
Log10(P) |
GO:0048469 |
cell maturation |
-5.5 |
GO:0007276 |
gamete generation |
-5.2 |
GO:0071695 |
anatomical structure maturation |
-5.2 |
|
 | |  |
| |
|
POSITIVELY (Full Connection)
GO |
Description |
Log10(P) |
R-HSA-6798695 |
Neutrophil degranulation |
-15.4 |
R-HSA-194315 |
Signaling by Rho GTPases |
-10.0 |
R-HSA-2262752 |
Cellular responses to stress |
-9.9 |
| | POSITIVELY (Keep MCODE Nodes Only)
Color |
MCODE |
GO |
Description |
Log10(P) |
|
MCODE_1 |
R-HSA-6809371 |
Formation of the cornified envelope |
-11.8 |
|
MCODE_1 |
GO:0030216 |
keratinocyte differentiation |
-11.5 |
|
MCODE_1 |
GO:0009913 |
epidermal cell differentiation |
-10.5 |
|
MCODE_2 |
R-HSA-9637690 |
Response of Mtb to phagocytosis |
-6.6 |
|
MCODE_2 |
R-HSA-9635486 |
Infection with Mycobacterium tuberculosis |
-6.4 |
|
MCODE_2 |
M210 |
PID IL8 CXCR2 PATHWAY |
-6.1 |
|
MCODE_3 |
R-HSA-450531 |
Regulation of mRNA stability by proteins that bind AU-rich elements |
-5.4 |
|
MCODE_3 |
R-HSA-4086400 |
PCP/CE pathway |
-5.4 |
|
MCODE_3 |
GO:0042176 |
regulation of protein catabolic process |
-5.2 |
|
MCODE_4 |
GO:0072659 |
protein localization to plasma membrane |
-4.8 |
|
MCODE_4 |
GO:1990778 |
protein localization to cell periphery |
-4.6 |
|
MCODE_4 |
R-HSA-9012999 |
RHO GTPase cycle |
-3.8 |
|
 | |  |
| |
|
All lists merged Colored by Counts(Full Connection)
GO |
Description |
Log10(P) |
R-HSA-6798695 |
Neutrophil degranulation |
-15.4 |
R-HSA-194315 |
Signaling by Rho GTPases |
-10.0 |
R-HSA-9716542 |
Signaling by Rho GTPases, Miro GTPases and RHOBTB3 |
-9.8 |
| | All lists merged Colored by Counts(Keep MCODE Nodes Only)
Color |
MCODE |
GO |
Description |
Log10(P) |
|
MCODE_1 |
R-HSA-6809371 |
Formation of the cornified envelope |
-11.8 |
|
MCODE_1 |
GO:0030216 |
keratinocyte differentiation |
-11.5 |
|
MCODE_1 |
GO:0009913 |
epidermal cell differentiation |
-10.5 |
|
MCODE_2 |
R-HSA-9637690 |
Response of Mtb to phagocytosis |
-6.6 |
|
MCODE_2 |
R-HSA-9635486 |
Infection with Mycobacterium tuberculosis |
-6.4 |
|
MCODE_2 |
M210 |
PID IL8 CXCR2 PATHWAY |
-6.1 |
|
MCODE_3 |
R-HSA-5617472 |
Activation of anterior HOX genes in hindbrain development during early embryogenesis |
-4.7 |
|
MCODE_3 |
R-HSA-5619507 |
Activation of HOX genes during differentiation |
-4.7 |
|
MCODE_3 |
GO:0009267 |
cellular response to starvation |
-4.2 |
|
MCODE_4 |
R-HSA-450531 |
Regulation of mRNA stability by proteins that bind AU-rich elements |
-5.4 |
|
MCODE_4 |
R-HSA-4086400 |
PCP/CE pathway |
-5.4 |
|
MCODE_4 |
GO:0042176 |
regulation of protein catabolic process |
-5.2 |
|
MCODE_5 |
hsa04727 |
GABAergic synapse |
-11.4 |
|
MCODE_5 |
hsa04914 |
Progesterone-mediated oocyte maturation |
-8.4 |
|
MCODE_5 |
hsa04915 |
Estrogen signaling pathway |
-7.8 |
|
 | |  |
| |
|
All lists merged Colored by Cluster(Full Connection)
GO |
Description |
Log10(P) |
R-HSA-6798695 |
Neutrophil degranulation |
-15.4 |
R-HSA-194315 |
Signaling by Rho GTPases |
-10.0 |
R-HSA-9716542 |
Signaling by Rho GTPases, Miro GTPases and RHOBTB3 |
-9.8 |
| | All lists merged Colored by Cluster(Keep MCODE Nodes Only)
Color |
MCODE |
GO |
Description |
Log10(P) |
|
MCODE_1 |
R-HSA-6809371 |
Formation of the cornified envelope |
-11.8 |
|
MCODE_1 |
GO:0030216 |
keratinocyte differentiation |
-11.5 |
|
MCODE_1 |
GO:0009913 |
epidermal cell differentiation |
-10.5 |
|
MCODE_2 |
R-HSA-9637690 |
Response of Mtb to phagocytosis |
-6.6 |
|
MCODE_2 |
R-HSA-9635486 |
Infection with Mycobacterium tuberculosis |
-6.4 |
|
MCODE_2 |
M210 |
PID IL8 CXCR2 PATHWAY |
-6.1 |
|
MCODE_3 |
R-HSA-5617472 |
Activation of anterior HOX genes in hindbrain development during early embryogenesis |
-4.7 |
|
MCODE_3 |
R-HSA-5619507 |
Activation of HOX genes during differentiation |
-4.7 |
|
MCODE_3 |
GO:0009267 |
cellular response to starvation |
-4.2 |
|
MCODE_4 |
R-HSA-450531 |
Regulation of mRNA stability by proteins that bind AU-rich elements |
-5.4 |
|
MCODE_4 |
R-HSA-4086400 |
PCP/CE pathway |
-5.4 |
|
MCODE_4 |
GO:0042176 |
regulation of protein catabolic process |
-5.2 |
|
MCODE_5 |
hsa04727 |
GABAergic synapse |
-11.4 |
|
MCODE_5 |
hsa04914 |
Progesterone-mediated oocyte maturation |
-8.4 |
|
MCODE_5 |
hsa04915 |
Estrogen signaling pathway |
-7.8 |
|
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) |
|
COVID037 |
RNA_Sun_Calu-3_12h_Down |
16 |
7.20 |
-9.10 |
-5.40 |
|
COVID039 |
RNA_Sun_Calu-3_24h_Down |
14 |
6.30 |
-7.30 |
-3.90 |
|
COVID389 |
Interactome_Laurent_HEK293_24h_ORF9C |
13 |
5.90 |
-6.40 |
-3.30 |
|
COVID198 |
Ubiquitinome_Stukalov_A549-ACE2_24h_Down |
10 |
4.50 |
-5.70 |
-2.70 |
|
COVID131 |
Phosphoproteome_Stukalov_A549-ACE2_24h_Up |
12 |
5.40 |
-5.60 |
-2.70 |
|
COVID172 |
Proteome_Stukalov_A549_72h_ORF3_Down |
12 |
5.40 |
-5.60 |
-2.70 |
|
COVID236 |
Proteome_Klann_Caco-2_24h_Down |
12 |
5.40 |
-5.60 |
-2.70 |
|
COVID375 |
Interactome_Laurent_HEK293_24h_NSP4 |
12 |
5.40 |
-5.60 |
-2.70 |
|
COVID385 |
Interactome_Laurent_HEK293_24h_ORF7A |
12 |
5.40 |
-5.60 |
-2.70 |
|
COVID124 |
Interactome_Stukalov_A549_72h_ORF3 |
11 |
5.00 |
-4.80 |
-2.10 |
|
COVID199 |
Ubiquitinome_Stukalov_A549-ACE2_24h_Up |
11 |
5.00 |
-4.80 |
-2.10 |
|
COVID363 |
Interactome_Laurent_HEK293_24h_E |
11 |
5.00 |
-4.80 |
-2.10 |
|
COVID377 |
Interactome_Laurent_HEK293_24h_NSP6 |
11 |
5.00 |
-4.80 |
-2.10 |
|
COVID386 |
Interactome_Laurent_HEK293_24h_ORF7B |
11 |
5.00 |
-4.80 |
-2.10 |
|
COVID387 |
Interactome_Laurent_HEK293_24h_ORF8 |
11 |
5.00 |
-4.80 |
-2.10 |
|
COVID390 |
Interactome_Laurent_HEK293_24h_S |
11 |
5.00 |
-4.80 |
-2.10 |
|
COVID027 |
RNA_Lamers_intestinal-organoid_expansion_Down |
10 |
4.50 |
-4.60 |
-1.90 |
|
COVID235 |
Phosphoproteome_Klann_Caco-2_24h_Up |
10 |
4.50 |
-4.10 |
-1.50 |
|
COVID382 |
Interactome_Laurent_HEK293_24h_ORF3A |
10 |
4.50 |
-4.10 |
-1.50 |
|
COVID384 |
Interactome_Laurent_HEK293_24h_ORF6 |
10 |
4.50 |
-4.10 |
-1.50 |
|
Figure 7. Summary of enrichment analysis in TRRUST.
|
|
_PATTERN_ |
GO |
Description |
Count |
% |
Log10(P) |
Log10(q) |
|
TRR01256 |
Regulated by: SP1 |
13 |
5.90 |
-3.80 |
-1.40 |
|
TRR00280 |
Regulated by: ETS1 |
5 |
2.30 |
-3.40 |
-1.00 |
|
TRR00011 |
Regulated by: AR |
5 |
2.30 |
-3.00 |
-0.69 |
|
TRR00781 |
Regulated by: MYCN |
3 |
1.40 |
-2.30 |
-0.33 |
|
TRR00484 |
Regulated by: HIF1A |
4 |
1.80 |
-2.20 |
-0.24 |
|
TRR00125 |
Regulated by: CREB1 |
4 |
1.80 |
-2.10 |
-0.21 |
|
TRR00780 |
Regulated by: MYC |
4 |
1.80 |
-2.00 |
-0.15 |
|
Figure 8. Summary of enrichment analysis in Transcription Factor Targets14.
|
|
_PATTERN_ |
GO |
Description |
Count |
% |
Log10(P) |
Log10(q) |
|
M14948 |
NRF2 01 |
11 |
5.00 |
-5.20 |
-2.40 |
|
M30060 |
MCRS1 TARGET GENES |
5 |
2.30 |
-5.00 |
-2.20 |
|
M29976 |
FOXR2 TARGET GENES |
10 |
4.50 |
-5.00 |
-2.20 |
|
M40729 |
CUX1 TARGET GENES |
16 |
7.20 |
-4.60 |
-2.00 |
|
M11821 |
CEBPB 01 |
10 |
4.50 |
-4.50 |
-1.90 |
|
M30100 |
NR1I2 TARGET GENES |
11 |
5.00 |
-4.30 |
-1.70 |
|
M171 |
GCCATNTTG YY1 Q6 |
12 |
5.40 |
-4.00 |
-1.50 |
|
M30333 |
ZNF507 TARGET GENES |
15 |
6.80 |
-4.00 |
-1.50 |
|
M8812 |
SF1 Q6 |
9 |
4.10 |
-3.90 |
-1.40 |
|
M3403 |
GTGACGY E4F1 Q6 |
15 |
6.80 |
-3.90 |
-1.40 |
|
M40757 |
MXD1 TARGET GENES |
7 |
3.20 |
-3.70 |
-1.30 |
|
M10498 |
TGCGCANK UNKNOWN |
13 |
5.90 |
-3.60 |
-1.20 |
|
M29941 |
DLX2 TARGET GENES |
9 |
4.10 |
-3.50 |
-1.10 |
|
M30170 |
SNIP1 TARGET GENES |
15 |
6.80 |
-3.20 |
-0.88 |
|
M8004 |
TGASTMAGC NFE2 01 |
7 |
3.20 |
-3.20 |
-0.88 |
|
M30018 |
HOXD11 TARGET GENES |
6 |
2.70 |
-3.10 |
-0.79 |
|
M30011 |
HOXB6 TARGET GENES |
13 |
5.90 |
-3.00 |
-0.75 |
|
M40826 |
CIC TARGET GENES |
10 |
4.50 |
-3.00 |
-0.73 |
|
M7937 |
AP1 C |
8 |
3.60 |
-3.00 |
-0.71 |
|
M11820 |
TTGCWCAAY CEBPB 02 |
4 |
1.80 |
-2.90 |
-0.67 |
|
Figure 9. Summary of enrichment analysis in Cell Type Signatures.
|
|
_PATTERN_ |
GO |
Description |
Count |
% |
Log10(P) |
Log10(q) |
|
M40004 |
BUSSLINGER ESOPHAGEAL LATE SUPRABASAL CELLS |
17 |
7.70 |
-15.00 |
-11.00 |
|
M41679 |
TRAVAGLINI LUNG MESOTHELIAL CELL |
26 |
12.00 |
-12.00 |
-7.50 |
|
M41652 |
TRAVAGLINI LUNG PROXIMAL BASAL CELL |
25 |
11.00 |
-11.00 |
-7.30 |
|
M40010 |
BUSSLINGER GASTRIC ISTHMUS CELLS |
20 |
9.00 |
-9.70 |
-5.90 |
|
M40122 |
DESCARTES MAIN FETAL SQUAMOUS EPITHELIAL CELLS |
11 |
5.00 |
-8.50 |
-4.90 |
|
M40237 |
DESCARTES FETAL LUNG SQUAMOUS EPITHELIAL CELLS |
13 |
5.90 |
-8.30 |
-4.90 |
|
M41717 |
FAN OVARY CL15 SMALL ANTRAL FOLLICLE GRANULOSA CELL |
21 |
9.50 |
-7.80 |
-4.40 |
|
M41700 |
TRAVAGLINI LUNG OLR1 CLASSICAL MONOCYTE CELL |
22 |
10.00 |
-7.60 |
-4.20 |
|
M41703 |
FAN OVARY CL1 GPRC5A TNFRS12A HIGH SELECTABLE FOLLICLE STROMAL CELL |
15 |
6.80 |
-6.80 |
-3.50 |
|
M41715 |
FAN OVARY CL13 MONOCYTE MACROPHAGE |
16 |
7.20 |
-6.50 |
-3.30 |
|
M41697 |
TRAVAGLINI LUNG EREG DENDRITIC CELL |
18 |
8.10 |
-6.50 |
-3.30 |
|
M41751 |
RUBENSTEIN SKELETAL MUSCLE MYELOID CELLS |
14 |
6.30 |
-6.50 |
-3.30 |
|
M39174 |
MURARO PANCREAS ACINAR CELL |
20 |
9.00 |
-6.30 |
-3.20 |
|
M41748 |
RUBENSTEIN SKELETAL MUSCLE SATELLITE CELLS |
13 |
5.90 |
-6.30 |
-3.20 |
|
M40024 |
BUSSLINGER DUODENAL STEM CELLS |
13 |
5.90 |
-6.20 |
-3.20 |
|
M40299 |
DESCARTES FETAL STOMACH SQUAMOUS EPITHELIAL CELLS |
7 |
3.20 |
-6.20 |
-3.20 |
|
M39238 |
LAKE ADULT KIDNEY C19 COLLECTING DUCT INTERCALATED CELLS TYPE A MEDULLA |
13 |
5.90 |
-6.00 |
-3.00 |
|
M39269 |
HU FETAL RETINA RGC |
15 |
6.80 |
-6.00 |
-3.00 |
|
M41710 |
FAN OVARY CL8 MATURE CUMULUS GRANULOSA CELL 2 |
18 |
8.10 |
-5.80 |
-2.80 |
|
M39229 |
LAKE ADULT KIDNEY C10 THIN ASCENDING LIMB |
13 |
5.90 |
-5.60 |
-2.70 |
|
Figure 10. Summary of enrichment analysis in DisGeNET15.
|
|
_PATTERN_ |
GO |
Description |
Count |
% |
Log10(P) |
Log10(q) |
|
C0022596 |
Palmoplantar Keratosis |
8 |
3.60 |
-9.40 |
-5.80 |
|
C4551675 |
Keratoderma, Palmoplantar |
12 |
5.40 |
-8.40 |
-4.90 |
|
C0853087 |
Nail abnormality |
8 |
3.60 |
-7.50 |
-4.10 |
|
C0870082 |
Hyperkeratosis |
11 |
5.00 |
-7.10 |
-3.80 |
|
C0041834 |
Erythema |
12 |
5.40 |
-6.90 |
-3.60 |
|
C0037277 |
Skin Diseases, Genetic |
7 |
3.20 |
-6.70 |
-3.50 |
|
C0221270 |
Acanthosis |
6 |
2.70 |
-6.60 |
-3.30 |
|
C1847514 |
Postnatal microcephaly |
7 |
3.20 |
-6.40 |
-3.30 |
|
C0153381 |
Malignant neoplasm of mouth |
20 |
9.00 |
-6.10 |
-3.00 |
|
C0020758 |
Congenital ichthyosis |
7 |
3.20 |
-5.70 |
-2.70 |
|
C0221260 |
Dystrophia unguium |
7 |
3.20 |
-5.60 |
-2.70 |
|
C0220641 |
Lip and Oral Cavity Carcinoma |
19 |
8.60 |
-5.60 |
-2.70 |
|
C4551630 |
Ichthyosis Congenita I |
3 |
1.40 |
-5.40 |
-2.60 |
|
C1838625 |
Warburg Sjo Fledelius syndrome |
4 |
1.80 |
-5.30 |
-2.50 |
|
C0265962 |
Ichthyosis linearis circumflexa |
6 |
2.70 |
-5.10 |
-2.30 |
|
C1334015 |
High Grade Intraepithelial Neoplasia |
5 |
2.30 |
-5.10 |
-2.30 |
|
C0020678 |
Hypotrichosis |
6 |
2.70 |
-4.90 |
-2.20 |
|
C0011615 |
Dermatitis, Atopic |
18 |
8.10 |
-4.90 |
-2.20 |
|
C0079153 |
Hyperkeratosis, Epidermolytic |
4 |
1.80 |
-4.90 |
-2.20 |
|
C0020757 |
Ichthyoses |
9 |
4.10 |
-4.80 |
-2.10 |
|
Figure 11. Summary of enrichment analysis in PaGenBase16.
|
|
_PATTERN_ |
GO |
Description |
Count |
% |
Log10(P) |
Log10(q) |
|
PGB:00156 |
Tissue-specific: Tongue |
9 |
4.10 |
-12.00 |
-7.50 |
|
PGB:00017 |
Tissue-specific: skin |
16 |
7.20 |
-11.00 |
-7.50 |
|
PGB:00081 |
Cell-specific: Bronchial Epithelial Cells |
9 |
4.10 |
-6.10 |
-3.00 |
|
PGB:00005 |
Tissue-specific: tonsil |
3 |
1.40 |
-2.00 |
-0.13 |
|
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