Network Query Search

Network Query Results

The results page contains following components:

The default network visualization has three panels. The left panel allows you to customize the network layout, the central panel visualize the network, and the right panel allows you to check edge/node information when you click an edge/node.

Advanced Functions

Unmapped Genes

If there are unmatched queried gene IDs, you can check the unmatched IDs by clicking the 'Unmapped IDs' button.

Download

You can download the gene-gene association cosine similarity score matrix in .csv format or the network graph in .png format.

Community Detection

You can perform the community detection among genes to find gene clusters.

Community GO Analysis

After running the community detection, you can perform a GO analysis on each gene community to find top GO terms associated with the community.

Change Community Color

After running the community detection, each gene cluster is highlighted with a distinct color. You can also change the cluster color using the color picker in each cluster page.

Global GO Analysis

You can run a global GO analysis to find top GO terms associated with queried genes. This is determined by calculating the average p-values of gene-GO associations among all queried genes.

Tab Menu

The 'Community Detection' and 'Global GO Analysis' will appear when corresponding advanced functions are ran.

Network

You can view the network visualization in the network tab.

Network Data View

You can view the gene-gene associations and their cosine similarity scores in a long table format or a matrix format.

Network Customization

Cosine Similarity

The gene-gene association network is constructed based on cosine similarity scores. Two genes are linked by an edge if their cosine similarity score is larger than a threshold (default:0.5). You can change the cosine similarity threshold to modify the network. In addition, you can choose the threshold by percentiles.

Find A Gene

You can zoom the network to a specific gene by using the 'Find A Gene' function. The found gene node is highlighted with a orange border.

Network Layout

You have following options to change the network layout:

Edge/Node Information

You can check edge/node information when clicking an edge/node. We provide following information for edge/node:

Shared GO Terms

You can check shared GO terms between two genes when clicking on an edge. You can click the 'Checked Shared GOs' button to run the check function. This will display the top GO terms shared by two genes.

Gene Query Search

Gene query function allow you to obtain a list of genes and get associated GO terms for each gene. Currently, only HGNC IDs are supported for searching. We provide an ID mapper function to map other gene names/synonyms to HGNC IDs.

Gene Query Results

The results page contains following components:

Unmapped Genes

If there are gene IDs unmatched during the search, the gene IDs are displayed in a red box.

Gene-GO Query Search

Gene-GO query function allow you to query a p-value matrix among a list of genes and a list of GO terms. Currently, we only support for searching genes using HGNC IDs and searching GO terms using GO IDs. We provide an ID mapper function to map other gene names/synonyms to HGNC IDs.

Alternatively, you can choose a specific number of GO terms to query the gene-GO association matrix, or use the entire GO terms to construct the matrix.

Gene-GO Query Results

You can view gene-GO associations in a long table format or matrix format. You can download the p-value matrix in a csv file.

ID Mapper Search

Supported Identifiers

ID Mapper Results

Results table display all mapped IDs, along with your queried term, gene symbol and name of mapped terms. Duplicated mappings are highlighted in yellow, you can check the box to determine which one to use. Afterwards, you can copy all terms to clipboard by clicking the 'Copy Selected' button.

Find Similar Genes

If no matched results are found for your queried term, you can use the 'Search for Similar Terms' function to identify similar terms.

After you download the ‘P-Value Matrix’ output from the GAIL web interface, you can load this file into the R environment using the R function read.csv() and the R function bayesGO() fits the bayesGO model by taking this data as input. Then, the R function predict() implements clustering of genes and GO terms and identifies association between genes and GO terms. Finally, the R function plot() visualizes the analysis results as below, where column and row side bars show gene and GO term cluster indices and red colors within the heatmap indicates stronger association between genes and GO terms. Please check Yu et al. (2018) for the step-by-step analysis guideline and Chung et al. (2017) for more details about the statistical model.