There are a few ways in which you can analyse chromatin immunoprecipitation (ChIP) data acquired from quantitative real-time polymerase chain reaction (qPCR). Two of the most common ways to report ChIP qPCR are: percentage of input and fold enrichment.

For the example analysis, I will use the data below. These are qPCR results from a ChIP experiment by using an antibody of interest and a negative (IgG) antibody. The input sample used here is 2%, however, I will explain how to adjust the analysis to accept other input amounts. Instead of the negative IgG antibody sample, you can always replace this with a no antibody sample.

## Percentage of input

The percentage of input analysis represents the amount of DNA pulled down by using the antibody of interest in the ChIP reaction, relative to the amount of starting material (input sample).

### How to calculate the percentage of input

- After performing the qPCR, firstly average the Ct values for each antibody used.

2. Next, we need to adjust the Ct value for the input sample. At the minute this input sample represents 2% of the DNA amount used, therefore we need a value that represents 100% of the DNA amount. To do this, we need to subtract the log of the dilution factor used from the average Ct of the 2% input. In the example we have used a 2% input sample, therefore this is a 50 dilution factor. If a 1% input sample was used, this would be a dilution factor of 100 etc. When log-transforming the data, ensure this is done with a base set at 2. So, in Microsoft Excel the formula would be:

=LOG(Your dilution factor, 2)

The ‘**2**‘ in the formula represents the base in the log calculation, always leave this as ‘**2**‘.

In the example with a 2% input sample, this would be:

=LOG(50, 2) =5.64

Now, subtract 5.64 from the average Ct of the 2% input to calculate the adjusted input Ct value. Doing this gives a value of ‘**24.2**‘. I have added this to the results table below.

3. The next step is to create delta Ct (i.e. the difference in Ct values between the ‘**adjusted input**‘ and the antibodies of interest). To do this, simply subtract the Ct values of the antibodies of interest from the ‘**adjusted input**‘ Ct value. I have done this in a new column called ‘**Delta Ct**‘.

4. Finally, we can calculate the % of input value based on the delta Cts. To do this, we do 2 to the power of ‘**Delta Ct**‘. Since the results are expressed as a percentage, we also need to multiply this by 100. In Excel, the formula to use is:

=100*2^(Delta Ct)

Just replace the Delta Ct with your own delta Ct values. In the above example, we will get the following results:

## Fold enrichment

Fold enrichment presents ChIP results relative to the negative (IgG) sample, in other words the signal over background. The negative sample is given a value of ‘**1**‘ and everything else will then be a fold change of this negative sample. As opposed to the percentage of input analysis, the fold enrichment does not require an input sample.

### How to calculate the fold enrichment

- Calculate the delta Ct for the difference between Ct values for the antibody of interest and the negative antibody. To do this, subtract the Ct for the negative antibody from the antibody of interest. Do this for all the samples.

Note that the ‘**Delta Ct**‘ for the negative antibody should always be ‘**0**‘.

2. To determine the fold enrichment do 2 to the power of negative ‘**Delta Ct**‘. In Excel, the formula to use is:

=2^-(Delta Ct)

Replace ‘**Delta Ct**‘ with your own delta Ct values. In the above example, we will get the following results:

Note that the ‘**Fold enrichment**‘ for the negative antibody should always be ‘**1**‘.

## ChIP qPCR analysis Excel template

For those still struggling with the analysis, or just want an easy template to use to quickly calculate the percentage of input and fold enrichment for you, I have created a Microsoft Excel template to freely download. The two different analysis can be found on separate sheets on the file and the instructions are at the top of each sheet.

Click here to download the ChIP qPCR data analysis template.