In addition, we can start finding relationships between the pathways or

between the terms.

Here we are concerned about finding the or prioritizing functional terms based

on their enrichment if we have a set of deferentially expressed genes or proteins.

So, this is the most simple and the most commonly applied test to

measure enrichment for a list of genes that were identified experimentally to

prioritize and rank the terms in those gene set libraries.

So for each set, we compute a P value that evaluates

the enrichment level of that term with your input list of genes.

So this is a contingency table problem.

You fill the table below with the information that represents the overlap

between the set in each of those gene set libraries, each of

those are rows in the files that we just looked at and your input gene list.

So you're looking for how many genes overlap between your set and

each row in those gene set libraries.

And that number goes on the top left.

And then you want to have a number of the number of

deferentially expressed genes that you identify.

And then the number of genes in the set that is the number of genes in each row.

And then some or the number of genes in the gene set library and

that number would be the deno, denominator.

And this will be in the bottom right square of this contingency table.

Now, using the Fisher Exact Test we can compute

the probability for overlap, when compare this to the binomial

probability of filling this table for random data and

by plugging in the numbers, as you see here in an example from MathWorld,

you can compute R1 and R2, which are the sum of the rows.

And C1, C2, which is the sum of the columns.

And then you can compute N, which is the total sum for

all the genes in all the four squares.

And then we can have once we have R1, R2 and C1,

C2 we can plug them into this formula.

Give us a probability of what is the chance of seeing that match overlap for

the gene set that's we query against in our input gene set.

So we have implemented this approach or tool called Enrichr.

And Enrichr has been a very popular tool.

Every day, there are about between 100 to 200 lists

that people upload to the system.

What Enrichr also has which is very powerful is various types of

visualization capabilities that use that generate vector

graphic images that are exportable for publications.

Now I'm going to show you a live demo of Enrichr.

So first, you can just type in Google, Enrichr.

Notice that it's enrich and r without the e.

And then you get link and this will take you to the website.

This is the upload part of the website.

Here you put in your list of genes.

If you don't have a gene list you can use the example.

And you can click on try regular example.

And you can also upload files with gene sets by using the Choose File button.

So once you uploaded your list of genes,

it automatically tells you how many genes you entered.

And also you have an option to fill in a name for your list.

So once you upload [SOUND] the gene list, you press the arrow key here.

And that executes the enrichment analysis.

So immediately,

we are shown the transcription category of gene set libraries.

And now we can start looking through the results by clicking on

each of those categories.

For example, for ChEA, we just click on the word ChEA.