Metascape Gene List Analysis Report

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Bar Graph Summary

Figure 1. Bar graph of enriched terms across input gene lists, colored by p-values.
The top-level Gene Ontology biological processes can be viewed here.

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 35 35

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, 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 distribution2, and q-values are calculated using the Benjamini-Hochberg procedure to account for multiple testings3. Kappa scores4 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 3 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:0048167 GO Biological Processes regulation of synaptic plasticity 4 11.43 -3.92 0.00
GO:0070555 GO Biological Processes response to interleukin-1 3 8.57 -3.61 0.00
hsa04080 KEGG Pathway Neuroactive ligand-receptor interaction 4 11.43 -3.08 0.00

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: STRING6, BioGrid7, OmniPath8, InWeb_IM9.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) algorithm10 has been applied to identify densely connected network components.

Quality Control and Association Analysis

Gene list enrichments are identified in the following ontology categories: 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 3-6. The algorithm used here is the same as that is used for pathway and process enrichment analysis.

Figure 3. Summary of enrichment analysis in Cell Type Signatures11.


GO Description Count % Log10(P) Log10(q)
M39068 MANNO MIDBRAIN NEUROTYPES HDA1 6 17.00 -4.30 0
M39070 MANNO MIDBRAIN NEUROTYPES HNBGABA 6 17.00 -3.90 0
M39072 MANNO MIDBRAIN NEUROTYPES HSERT 5 14.00 -3.80 0
M39067 MANNO MIDBRAIN NEUROTYPES HDA 5 14.00 -3.60 0
M39069 MANNO MIDBRAIN NEUROTYPES HDA2 5 14.00 -3.50 0
M40149 DESCARTES FETAL ADRENAL SYMPATHOBLASTS 3 8.60 -3.50 0
M39161 GAO LARGE INTESTINE ADULT CA ENTEROENDOCRINE CELLS 4 11.00 -3.30 0
M40229 DESCARTES FETAL LIVER MYELOID CELLS 3 8.60 -2.70 0
M39066 MANNO MIDBRAIN NEUROTYPES HNBML5 4 11.00 -2.70 0
M39168 MURARO PANCREAS ALPHA CELL 4 11.00 -2.40 0
M39065 MANNO MIDBRAIN NEUROTYPES HRN 3 8.60 -2.20 0
M39052 MANNO MIDBRAIN NEUROTYPES HOPC 3 8.60 -2.10 0
Figure 4. Summary of enrichment analysis in DisGeNET12.


GO Description Count % Log10(P) Log10(q)
C0001973 Alcoholic Intoxication, Chronic 5 14.00 -3.30 0
C0013170 Drug habituation 3 8.60 -2.80 0
C0017601 Glaucoma 5 14.00 -2.70 0
C0038586 Substance Use Disorders 3 8.60 -2.70 0
C0006012 Borderline Personality Disorder 3 8.60 -2.70 0
C1510472 Drug Dependence 3 8.60 -2.50 0
C0039483 Giant Cell Arteritis 3 8.60 -2.50 0
C0007682 CNS disorder 3 8.60 -2.20 0
C0007786 Brain Ischemia 3 8.60 -2.10 0
C0279671 Cervical Squamous Cell Carcinoma 3 8.60 -2.10 0
C0677932 Progressive Neoplastic Disease 3 8.60 -2.00 0
C3539781 Progressive cGVHD 3 8.60 -2.00 0
Figure 5. Summary of enrichment analysis in PaGenBase13.


GO Description Count % Log10(P) Log10(q)
PGB:00032 Tissue-specific: Cerebellum 3 8.60 -3.20 0
Figure 6. Summary of enrichment analysis in Transcription Factor Targets.


GO Description Count % Log10(P) Log10(q)
M11934 SRF Q5 01 4 11.00 -3.90 0
M5479 SRF Q4 4 11.00 -3.90 0
M6885 AREB6 02 4 11.00 -3.70 0
M7023 CRX Q4 4 11.00 -3.60 0
M40745 ZNF140 TARGET GENES 5 14.00 -3.40 0
M19642 CDPCR1 01 3 8.60 -3.40 0
M10046 ATF B 3 8.60 -2.90 0
M11838 FOXD3 01 3 8.60 -2.80 0
M17997 TGACGTCA ATF3 Q6 3 8.60 -2.60 0
M5954 NFY C 3 8.60 -2.50 0
M3109 CEBP Q3 3 8.60 -2.50 0
M11370 CREBP1 Q2 3 8.60 -2.50 0
M6517 AAAYWAACM HFH4 01 3 8.60 -2.50 0
M16699 CREBP1CJUN 01 3 8.60 -2.50 0
M9955 TGAYRTCA ATF3 Q6 4 11.00 -2.40 0
M2054 AP1 Q6 01 3 8.60 -2.40 0
M17180 CREB 01 3 8.60 -2.40 0
M4803 NF1 Q6 3 8.60 -2.40 0
M11244 AREB6 01 3 8.60 -2.40 0
M12915 NF1 Q6 01 3 8.60 -2.40 0

Reference

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