Enrichr uses a list of Entrez gene symbols as input. Each symbol in the input must be on its own line. You can upload the list by either selecting the text file that contains the list or just simply pasting in the list into the text box.

It is recommended to enter a description for your list so that multiple lists can be differentiated from each other if you choose to save or share your list.

If you are using a touch device, you can swipe left or right to navigate between the different tabs at the top.

On the results page, the analysis is divided into different categories of enrichment; in the example, the transcription category is shown. On a mobile device, you can switch between the categories by swiping left or right. Within each category, the enrichment analyses of various gene-set libraries are listed.

You can open a particular analysis by tapping on the name of the gene-set library, presenting a multitude of visualizations. On a mobile device, you can switch between the visualizations by swiping left or right. To return to switching categories on a mobile device, tap the name of the gene-set library to close the analysis.

The first visualization is the bar graph. You can sort the bar graph by the different score methods by clicking on the bar graph.

The length of the bar represents the significance of that specific gene-set or term. In addition, the brighter the color, the more significant that term is.

You can export the bar graph as a figure by clicking on one of the image format buttons to the top right of the bar graph.

The data table gives you a raw view of the data. By clicking on the column header, you can sort the table by the term, p-value, z-score, or combined score. Furthermore, you can filter the results by searching for a specific term.

Hovering over each row shows you the genes from the input that were found to be associated with that term. If the term name is highlighted in red, it means that you can click on the term name for additional information from external sites.

You can also get the table information in tab-delimited format by clicking on the "Export to Table" button.

NOTE: The grid may not be available for all gene-set libraries.

Each grid square represents a term and is arranged based on its gene-set similarity with other terms. It shows only the top 10 terms sorted by combined score. The brighter the square, the more significant that term is. Clicking on the grid allows you to toggle to an alternate view that colors the grid based on its correlation score with neighbors with white dots representing the significant terms.

The z-score and p-value is a measure of how clustered the top 10 terms are on the grid

NOTE: The network may not be available for all gene-set libraries.

Each node represents a term and a link between two nodes means that the two terms have some gene content similarity.

Initially, the network is force directed, but if you drag the node to a fixed position, it will stay there.

Like the other SVG figures, the network can be exported in three image formats.

Enrichr makes it easy to share your results with others. Simply click on the share icon to the right of the description box. It will provide you with a temporary direct link to your analysis that you can share with others.

In addition, you can register to have a user account within Enrichr. Having an account enables permanently saving lists on our server so you can return to them without the need to re-upload. Once logged in, you would need to click the save or share button for your list to be automatically associated with your account.

By default, all the figures have a red color scheme. However, you can change the color scheme by clicking on the cog-shaped icon to bring up a color picker. Selecting a color will change the color scheme of the bar graph, grid, and network figures.

On the "Find A Gene" tab from the main Enrichr page, you can look up which gene-set library terms your gene of interest belongs to.

Logging in or clicking on your name/email in the top right corner of the page while already logged in will take you to the account page for Enrichr. This table lists all the analyses that you have saved thus far. You can further filter the table for a particular list using the search box. Clicking on the list name will take you to the analysis.

On the "Account Settings" tab of the same page, you can change account details if you need to update any of your information.

Enrichr implements three approaches to compute enrichment. The first one is a standard method implemented within most enrichment analysis tools: the Fisher exact test. This is a proportion test that assumes a binomial distribution and independence for probability of any gene belonging to any set. The second test is a correction to the Fisher exact test that we developed based on intuition. We first compute enrichment using the Fisher exact test for many random gene sets in order to compute a mean rank and standard deviation from the expected rank for each term in the gene-set library. Then using a lookup table of expected ranks with their variances, we compute a z-score for deviation from this expected rank, this can be a new corrected score for ranking terms. Alternatively, we combined the p-value computed using the Fisher exact test with the z-score of the deviation from the expected rank by multiplying these two numbers as follows:

c = log(p) × z

Where c is the combined score, p is the p-value computed using the Fisher exact test, and z is the z-score computed to assess the deviation from the expected rank. Enrichr provides all three options for sorting enriched terms. In the results section, we show how we evaluated the quality of each of these three enrichment methods by examining how the methods rank terms that we know should be highly ranked.

Enrichr is in active development so it is possible that something can break during our updates. If it is a cosmetic bug, please try refreshing your browser (by pressing Ctrl+F5/Shift+F5/Command+F5). If that does not fix the problem, please send us your input file and how you reproduced the bug to help us fix the problem. When reporting a bug, please also include screenshots and the browser that you used. You can find our contact email on the about page.

Since we are always looking for ways to improve Enrichr, please use our contact email on the about page to send us feature suggestions.

Enrichr uses SVG to generate the figures and since Internet Explorer (IE) versions prior to IE 9 do not render SVG properly, Enrichr does not work with these browsers. In addition, the stock browser in Android 2.3.7 (Gingerbread) or below does not support SVG either; however, Firefox for Android and Opera for Android are viable alternatives. You can see a complete table of SVG compatibility across various browsers here.

You can include Enrichr on your site with some simple JavaScript:

function enrich(options) {
	var defaultOptions = {
		description: "",
		popup: false
	};

	if (typeof options.description == 'undefined')
		options.description = defaultOptions.description;
	if (typeof options.popup == 'undefined')
		options.popup = defaultOptions.popup;
	if (typeof options.list == 'undefined')
		alert('No genes defined.');

	var form = document.createElement('form');
	form.setAttribute('method', 'post');
	form.setAttribute('action', 'http://amp.pharm.mssm.edu/Enrichr/enrich');
	if (options.popup)
		form.setAttribute('target', '_blank');
	form.setAttribute('enctype', 'multipart/form-data');

	var listField = document.createElement('input');
	listField.setAttribute('type', 'hidden');
	listField.setAttribute('name', 'list');
	listField.setAttribute('value', options.list);
	form.appendChild(listField);

	var descField = document.createElement('input');
	descField.setAttribute('type', 'hidden');
	descField.setAttribute('name', 'description');
	descField.setAttribute('value', options.description);
	form.appendChild(descField);

	document.body.appendChild(form);
	form.submit();
	document.body.removeChild(form);
}				

To use it, simply call enrich({list: genes}) in your JavaScript and pass in genes as a list of Entrez Gene symbols separated by newlines. You can include a description for the list by using enrich({list: genes, description: descString}). To have the results pop up in a new window, use enrich({list: genes, popup: true}).

We have provided a simple python script to take the cuffdiff output from Cufflinks, find the significant genes of all the comparisons, and run it through Enrichr.

To run this script, you have to have Python 2.7.3 installed and Python library, poster. The library can also be easily installed using easy_install.

To run the script on the example file, open command line and go to the directory where the script is stored and type python cuffdiff2links.py example.diff. Press Enter to run the script.

After successfully running the script, two files, updown.txt and enrichrLinks.txt, will be generated. updown.txt contains the significant genes of all the comparisons and enrichrLinks.txt contain the links to Enrichr that you can copy and paste into your browser to see the result.