Welcome to the tutorials page. Here you will find detailed guides for using scGRNdb's analysis pipelines.
Overview
scGRNdb provides 4 core functions:
- Network Browser: Browse available cell type GRNs and query your genes of interest.
- Network Prioritization: Query your genes of interest against the scGRNdb database to find cell type GRNs and driver genes that best model your data.
- Network Pathway Annotation: Identify modular components in your own network and functionally annotate them with pathway and disease databases.
- Network Comparison: Compare networks for similar network structures.
Network Browser
This section allows you to browse and visualize available gene regulatory networks in scGRNdb.
Step 1: Browse Available Networks
The network table provides all the available GRNs in scGRNdb. You can filter networks by species (human or mouse), tissue, and cell type, as well as the scRNAseq data atlas used to generate the network. Once you selected your search criteria, click on up to 2 table entries, and the input forms will automatically populate with your choices.
After selecting the networks, you can add each network to the network visualization by clicking the "Add Network" button. Then you can explore the network in 3 ways:
- Module View: An overall view of the network structure. This is the first view upon adding the network.
- Gene Search View: Input either a list of genes or a file of genes to search for in the network. The modules that contain your genes will be highlighted in the network, and you can click them to explore in more detail. You can also click the Search Tab to view the direct neighbors of your genes.
- Module-Specific Gene View: Click on any module or use the module search input to explore the biological annotations of the module and view the genes in the module.
There are a couple of styling options available to filter the network for ease of visualization:
- Filter edges by weight (Gene Search and Module-Specific Gene View only)
- Filter nodes by degree (Gene Search and Module-Specific Gene View only)
- Refresh layout whenever you adjust the filtering parameters
- Expand the search depth from your input genes network (Gene Search View only)
Example Input Gene File
| GENE1 |
| GENE2 |
| GENE3 |
| GENE4 |
| GENE5 |
| GENE6 |
| GENE7 |
| GENE8 |
Step 2: Visualize the Network
Module View
This is an overall view of the network structure and the first view upon adding the network. The size of the nodes (modules) will be proportional to the number of genes in the module, and the edges will be weighted by the number of outgoing edges from the module.
Gene Search View
From the Module View you can input a list or file of genes to search in the network. The modules that contain your genes will be highlighted in the network, and you can click them to explore in more detail. You can also click the Search Tab to view the direct neighbors of your genes.
There are a couple of styling options available:
- Adjust node size based on degree.
- Filter edges by weight.
- Refresh layout whenever you adjust the filtering parameters.
- Expand the search depth from your input genes network.
Module-Specific Gene View
From the Module View you can click on any module or use the module search input to explore the biological annotations of the module and view the module-specific genes.
There are a couple of styling options available:
- Adjust node size based on degree.
- Filter edges by weight.
- Refresh layout whenever you adjust the filtering parameters.
Step 3: Export the Network
After you are satisfied with the network visualization, you can export the network as a .json file by clicking the "Export Network" button. This will download a .json file with the network structure.
Network Prioritization Pipeline
This pipeline allows you to model your gene set against cell type GRNs in scGRNdb and identify the cell type specific mechanisms that best explain your data.
Step 1: Prepare Your Gene Set File
The main input for the analysis is one or more gene sets. If you have one gene set, you can provide it as a comma-separated list of genes, or as txt file. If you have multiple gene sets, you can provide it as a txt file. If you provide a txt file, it should have the following columns:
genes: Gene names (HGNC/MGI symbol)module: Gene set name
Example Gene Set File
| genes | module |
|---|---|
| GENE1 | module1 |
| GENE2 | module1 |
| GENE3 | module1 |
| GENE1 | module2 |
| GENE4 | module2 |
| GENE3 | module3 |
Step 2: Select Species and Atlas
The next step is to select the species (human or mouse) and their corresponding scRNAseq atlases used to generate the GRNs. You can select as many atlases as you want. For brain tissues, we recommend selecting any of the Allen Brain Atlases. For other tissues, we recommend Tabula Sapiens and GTEx for human and Tabula Muris for mouse.
scRNAseq Data Atlases
| Human | Mouse |
|---|---|
| Allen Brain Atlas (10X) | Allen Brain Atlas (10X) |
| Allen Brain Atlas (SmartSeq) | Allen Brain Atlas (SmartSeq) |
| Tabula Sapiens | Tabula Muris (10X) |
| Human Cell Landscape | Tabula Muris (SmartSeq) |
| GTEx | Tabula Muris Senis (10X) |
| Tabula Muris Senis (SmartSeq) | |
| Mouse Cell Atlas |
Step 3 (Optional): Provide your Email
If you provide your email, you will receive an email notification when the analysis is complete. If you do not provide an email, remember to save your sessionID to retrieve your results later.
Step 4: Submit and Monitor
Click Submit to start the analysis. You can monitor the progress of the analysis in the Review Files tab. If you provided an email, you will receive an email notification when the analysis is complete.
Step 5: Explore and VisualizeResults
Downloads
Once the analysis is complete, you can download the results in the downloads table:
- Enriched Networks - A .txt file listing the gene set and their enriched networks.
Enriched Networks Table
The Enriched Networks file is also displayed as a table below the downloads table. Here is a description of the columns:
- ACTIONS - Visualze the network module and overlapping genes in the Network Browser Tool
- ID - Unique ID
- GENESET - Name of gene set
- NETWORK TISSUE - Tissue of the enriched GRN
- NETWORK CELLTYPE - Cell Type of the enriched GRN
- NETWORK MODULE - GRN subnetwork with enrichment for gene set
- NETWORK CELLTYPE - scGRNdb cell atlas of the enriched GRN
- P - P-value calculated using the hypergeometric test
- FDR - False Discovery Rate
- RISK RATIO - Enrichment score
- GENESET SIZE - Number of genes in the gene set
- NETWORK MODULE SIZE - Number of genes in the GRN module
- OVERLAP - Number of overlapping genes between the GRN module and the gene set
You can filter the results by any column. The most common filtering would be to identify your geneset, sort the FDR column, filter to any tissue or cell type of interest, and select your networks.
You can also visualize the network module and overlapping genes in the Network Browser Tool by clicking the "Visualize" button in the ACTIONS column. This will automatically populate the network visualization with the network module and overlapping genes.
Step 6: Key Driver Analysis
Review the results table and choose networks for Key Driver Analysis (KDA). You can select as many networks as you want. When you click "Prepare KDA", you will be redirected to the KDA tab, where you can review networks you selected. Each unique network will have its own KDA run, and their mapped genesets will be combined into one file. Then, you can click Run KDA, which will take you to the KDA analysis page on Mergeomics Web Server. Your session will carry over to the Mergeomics Web Server with all input files and recommended parameters already set. All you will need to do is provide your email and click submit.
We recommend the default parameters for KDA. More details about the KDA parameters can be found on the Mergeomics tutorial page.
Network Pathway Annotation
This pipeline helps you identify functional modules in your own gene network and connect them to biological pathways and disease gene signatures.
Step 1: Select a Network
The main input for the analysis is a network file. It can be a network that you generated or a sample network provided. The network file should have the following columms:
HEAD: Source gene (HGNC/MGI symbol)TAIL: Target gene (HGNC/MGI symbol)WEIGHT: Edge weight (numeric value)
Example Network File
| HEAD | TAIL | WEIGHT |
|---|---|---|
| GENE1 | GENE2 | 0.1 |
| GENE1 | GENE3 | 1 |
| GENE4 | GENE3 | 0.75 |
Step 2: Select Module Parameters
The module detection algorithm will find the densely connected subgraphs in the network. It is based on Leiden clustering, which detects communities in the network by optimizing a modularity score. Since we want to analyze the function of the genes within the modules, we need to control the number of genes in the modules to provide interpretable pathway enrichment results. To do this, you can set the following parameters:
- Minimum module size (recommended default: 10 genes)
- Maximum module size (recommended default: 300 genes)
Step 3: Select Species and Pathway Databases
The next step is to select the species (human or mouse) and pathway databases for enrichment analysis. We have collected a list of pathway databases for each species, and you can select one or more of them. For sample data, we recommend starting with GO Biological Process and DisGeNET.
Pathway Databases
| GO Biological Process | KEGG |
| GO Cellular Component | Reactome |
| GO Molecular Function | Biocarta |
| DisGeNET | GWAS Catalog |
Step 4 (Optional): Provide your Email
If you provide your email, you will receive an email notification when the analysis is complete. If you do not provide an email, remember to save your sessionID to retrieve your results later.
Step 5: Submit and Monitor
Click Submit to start the analysis. You can monitor the progress of the analysis in the Review Files tab. If you provided an email, you will receive an email notification when the analysis is complete.
Step 6: Explore and Visualize Results
Downloads
Once the analysis is complete, you can download the results in the downloads table:
- Modules - A .txt file listing all genes and their associated modules
- Pathway Enrichment - A .txt file with the full enrichment analysis results
Pathway Enrichment Table
The Pathway Enrichment file is also displayed as a table below the downloads table. Here is a description of the columns:
- ACTIONS - Browse the network genes and modules in the Network Browser Tool
- ID - Unique ID
- MODULE ID - Identifier for each module
- PATHWAY - Name of the enriched pathway
- PATHWAY SOURCE - Database used for pathway enrichment
- P - P-value calculated using the hypergeometric test
- FDR - False Discovery Rate
- RISK RATIO - Enrichment score
- module_size - Number of genes in the module
- pathway_size - Number of genes in the pathway
- overlap - Number of overlapping genes between the module and the pathway
You can filter the results by module ID, size, or overlap. You can also adjust the number of rows displayed per page and download the entire table.
You can also browse the network genes and modules in the Network Browser Tool by clicking the "Visualize" button in the ACTIONS column. This will automatically populate the network visualization with the network module.
Network Comparison
This pipeline helps you compare the structure of 2 networks in scGRNdb or in your own network. Popular comparisons include comparing enriched gene modules in different cell types within a tissue, comparing cell type networks across tissues, and comparing network structures between species.
Step 1: Select 2 Networks
You can select 2 networks to compare in the Network Browser Tool, or from the Network Prioritization and Network Pathway Annotation pipeline results tables.The networks should be in the same format as the Step 1 input networks.
Step 2: Compare Networks
When 2 networks visualized in Gene Search View or Module-Specific Gene View, you can compare their network structures side by side, or via the combined network view. Click the "Combine Networks" button for a union of the 2 networks in their current filtered state. The first network's nodes and edges will be colored in red, the second in blue, and the shared in green. The same styling and export options are available as the Gene Search View.