DV Research Insights

Navigating Gene Analysis with Ease: A Step-by-Step Guide to Using Enrichr

IEmbarking on gene analysis can seem daunting, especially if you’re new to the world of bioinformatics or lack extensive coding skills. That’s why we’ve crafted a comprehensive guide to using Enrichr, a user-friendly, web-based tool that simplifies this process for students and researchers alike.

Damir Vareslija
4 minutes

Welcome to our latest blog post, where we’re excited to share a user-friendly protocol for conducting pathway analysis using the Enrichr tool. This protocol is designed specifically for students and researchers with minimal coding experience, guiding you through a straightforward process to analyze gene lists and uncover vital insights.

Enrichr is a web-based software, freely accessible and incredibly powerful for biological data analysis. My favourite resource from the wizards of the Maayan lab (https://labs.icahn.mssm.edu/maayanlab/). Whether you’re an undergraduate just starting in the lab or a postgraduate looking to delve deeper into your research, this step-by-step guide will take you from inputting your gene list to visualizing your data in a comprehensive, easy-to-understand manner.

Our Enrichr “Pipeline” includes:

  1. Inputting Your Gene List: We start by showing you how to input your gene list into Enrichr, setting the foundation for your analysis.
  2. Pathway Analysis Options: Whether you’re looking at individual sources like KEGG or merging various outputs for a broader view, we’ve got you covered.
  3. Accessing Reliable Sources: We’ll navigate you through Enrichr’s various tabs, highlighting key sources for different types of analysis, from pathways to transcription factors.
  4. Extracting and Organizing Data: Learn how to export data into Excel for detailed analysis, and how to organize this information effectively.
  5. Visualizing Your Findings: Finally, we’ll guide you through creating a graph in GraphPad Prism to visualize your results, making your data not just accessible but also visually impactful.

Enrichr “Pipeline”

1. Begin by identifying your gene list of interest and input it into Enrichr. https://maayanlab.cloud/Enrichr/

2. If you require a general pathway analysis and wish to generate a combined single figure ranked by odds ratio or p-value, you can merge various Enrichr outputs to create your list. Alternatively you can just focus on individual Sources (eg KEGG).

3a. Navigate to the “Pathways” tab and refer to the following reliable sources for checking and downloading: I. KEGG 2021 Human II. MSigDB Hallmark 2020 III. WikiPathway 2021 Human IV. BioPlanet 2019 V. Reactome 2022 Under Ontologies Tab access: I. GO Biological Process 2021 II. GO Molecular Function 2021 III. GO Cellular Component 2021 Under Diseases Drugs tab go use only (i) MSigDB Oncogenic Signatures

3b. For analyzing transcription and potential regulators of your gene list, access the “Transcription” tab, focusing on ChEA 2022, ENCODE and ChEA Consensus. Keep this separate from your pathways list.

4. To extract the Excel list for each pathway, click on the pathway of interest. In the sub-tab section, go to the table and select “Export entries to table.” Open the exported table in Excel, which will provide p-value, adjusted p-value (significance), odds ratio, and the genes scored for the indicated pathways.

5. Create a source tab where you indicate the origin of the list (e.g., MSigDB). Generate a master Excel file with the first tab containing information on the input genes, the date Enrichr was accessed, and any other necessary details for replication.

6. Repeat the above steps for each downloaded pathway and add them to the main Excel file, inserting them below the previous list and noting the source.

7. After completion, insert a tab for the “-log10(p-value).” Use the formula =-LOG10(p-value number) in the respective cells. Ensure that these cells are formatted to display numbers rather than scientific notation for ease of use. Drag the formula down. At this stage, consider ordering your master Excel file and filtering the adjusted p-value column from lowest to highest. The significance cutoff is set at P < 0.05. This will aid in marking statistically significant points in your GraphPad. 8. Open GraphPad Prism and select “New Data Table and Graph.” Use the Odds Ratio for the X-axis and the “-log10(*p-value)” for the Y-axis (A). Your row titles will represent the pathways. Highlight all the rows that correspond to p-adjusted value significance and format them in a distinct colour for easy identification on the graph. Additionally, you can adjust the size of the points based on the level of significance. There are numerous customization options available, and you may also choose to display the names of select pathways of interest on the graph.

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