Mergeomics Tutorial

Mergeomics is a flexible and streamlined pipeline that is able to retrieve meaningful biological insight from multiple types of omics data using multiple levels of analysis. Users can easily build their workflow based on their specific data and desired analysis. To facilitate one's analysis, we provide many different types of sample files including SNP to gene mapping, linkage disequilibrium files, and biological networks.

The two core functions of Mergeomics are marker set enrichment analysis (MSEA) and key driver analysis (KDA). Depending on the 7data type, there are slightly different considerations for MSEA, and so we have segmented the tutorial based on the specific data from the user. From MSEA to KDA, biological markers from significant marker sets found in MSEA and a network is input into KDA. The user can also run KDA as a first step using a list of markers (i.e genes) (tutorial in 'List(s) of genes' button below).

Sample input files can be found here. Sample outputs can be found here.

In addition to this tutorial, we have also embedded instructions throughout the pipeline workflow itself. Look for this button:

**Please save your session ID which can be copied by clicking on it at the top of the left sidebar so that you may return to your session at a later time or we recommend to enter your email when prompted to receive session information and results! (valid for 48 hours)

For an in-depth tutorial on how one can use Mergeomics, click below on the data type you have.

Data input details

All files are recommended to be in UTF-8/ASCII encoded format.

Parameters details

Marker dependency filtering (MDF)

Marker set enrichment analysis (MSEA)

Key Driver Analysis (KDA)

Video Tutorials


File upload

Individual GWAS enrichment

Individual EWAS, TWAS, PWAS, or MWAS enrichment

Weighted Key Driver Analysis

To see descriptions on how the pipeline can be used, click on the use cases below.

Use case Data Analysis
1. What are the genetic mechanisms of autism spectrum disorder (ASD)? What are the key regulators of those gene sets associated with ASD? What drugs can be used to target these disease networks? GWAS MDF MSEA KDA PharmOmics
2. What functional gene sets are enriched for differentially expressed genes between high sucrose treated mice and untreated mice and do they overlap with type 2 diabetes GWAS? TWAS, GWAS Meta-MSEA
3. Which cell type specific differentially expressed genes (DEGs) of beta-amyloid aggregation mouse models are enriched for Alzheimer's disease GWAS? Gene lists, GWAS MSEA
4. What genes are key regulators for protein folding genes in a brain gene regulatory network? Single gene list KDA