**qPCR** is a sophisticated technology used to measure the amount of **DNA** in a sample by using **PCR**. **qPCR** stands for the term **quantitative polymerase chain reaction**. Though it is an advanced procedure, we can **analyze** the **qPCR** data in Excel. In this article, we will demonstrate to you **two** methods on how to analyze **qPCR** data in Excel. If you are curious to know them, download our practice workbook and follow us.

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## What Is qPCR Analysis?

**qPCR** or **quantitative polymerase chain reaction **is a sophisticated technology used to measure the amount of **DNA** in a sample by using **PCR (polymerase chain reaction)**. There are two ways to analyze qPCR data.

**Double Delta Ct Method**

In 2001, **Livak** and **Schmittgen** termed this analyzing procedure, the **Double Delta Ct** method. It is a specific case of the **Pfaffl** method. According to this method, we have to input the **two** average sets of experimental data (**Gene Tested Experimental** and **Housekeeping Gene Experimental**) and control data (**Gene Tested Control** and **Housekeeping Gene Control**). Using these values, we will get the values of **∆CTE** and **∆CTC**, respectively.

The value of **∆CTE** represents the deduction value of **Gene Tested Experimental (TE)** and **Housekeeping Gene Experimental (HE)**. The general expression of **∆CTE** is:

Similarly, the value of **∆CTC** stands for the deduction value of **Housekeeping Gene Control (HC)** from **Gene Tested Control (TC)**. The mathematical expression of this term is:

After that, we need to estimate the value of **∆∆Ct**. The formula to determine the value of **∆∆Ct** is:

Finally, we will evaluate the **Gene Expression Ratio**. According to this method, we assume the **Primer Efficiency** for both experimental and control genes is **100%**. Thus, the expression of the **Gene Expression Ratio** is:

**Pfaffl Method**

The **Pfaffl** method is a general method for **qPCR** analysis. This method has similarities with the **Double Delta Ct** method. However, the **Primer Efficiencies** value in this method is not **100%**. It can be any number. Usually, this value remains between **90%** to **110%** for both **House Keeping Gene (HKG)** and **Gene of Interest (GOI)**. In 2001, **Michael Pfaffl** offered this analysis formula in the **Nucleic Acids Research** journal.

In this approach, we have to input two sets of data. Using this data, we calculate their average value. Then, we estimate the average of the control samples. From this, we will determine the value of **∆Ct**. The expression of **∆Ct **is:

Moreover, the mathematical formula to analyze the **Gene Expression Ratio** is:

## 2 Easy Ways to Analyze qPCR Data in Excel

In this contest, we are going to analyze the **qPCR** data for **three** or **five** samples of data. We will first conduct the analyze for the **Double Delta Ct** method and then we will demonstrate the **Pfaffl method**.

### 1. Analyze qPCR Data Through Double Delta Ct Method

For analyzing the **qPCR** data through the **Double Delta Ct** method, we consider a dataset of **five** **DNA** samples. In this method, we have to consider the value of the **PCR Primer Efficiencies** for both the experimental gene and control gene is **100%**. We can also claim that this is a specific case of the **Pfaffl method.** The steps will analyze given as follows:

**📌 Steps:**

- First of all, input all the gene values accurately as shown in the image. We have to input all the experimental values of
**Gene Tested Experimental(TE)**and**Housekeeping Gene Experimental(HE)**in columns**B**and**C**Similarly, input all the control values of**Gene Tested Control(TC)**and**Housekeeping Gene Control(HC)**in columns**D**and**E**respectively.

- Now, in cell
**F5**, to calculate the value of**∆CTE**, write down the following formula.

`=B6-C6`

- Press
**Enter**.

- Similarly, to estimate the value of
**∆CTC**, write down the following formula in cell**G5**.

`=D6-E6`

- Again, press
**Enter**.

- Then, select cell
**H5**and write down the following formula to get the value of**∆∆Ct**.

`=F6-G6`

- Press the
**Enter**.

- Finally, to calculate the value of the
**Gene Expression Ratio**or**2^(−∆∆Ct)**, write down the following formula in cell**I5**.

`=2^(-H6)`

- Press
**Enter**for the last time.

- After that, select the range of cell
**F6:I6**.

**Double-click**on the**Fill Handle**icon to copy the formula up to row**10**.- You will get the values of the
**Gene Expression Ratio**for every sample.

Thus, we can say that our method worked perfectly, and we are able to analyze **qPCR** data in Excel.

** 🔍 Interpretation of the Result**

The value of the **Gene Expression Ratio** of **0.6507** in cell **I5** means the gene samples in the **tested conditions** with respect to the **control conditions** all have been normalized to our housekeeping gene. Moreover, you can consider it in the percentage term. **0.6507** means **65.07%** gene expression in our **tested condition** with our **control condition**.

**Read More: How to Analyze Large Data Sets in Excel (6 Effective Methods)**

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### 2. Analyze qPCR Using Pfaffl Method

In this approach, we will use the **Pfaffl method**. The main difference between this method with the **Double Delta Ct** method is in the value of **PCR Primer Efficiencies **for both the experimental gene and control gene which are not **100%**. In this example, we will assume the **Primer Efficiency** values for both cases. For the **House Keeping Gene** sample, we are presuming the value of **Primer Efficiency** is **93%**, whereas for **Gene of Interest **this value will be** 101%.** The steps of this method are given below:

**📌 Steps:**

- At first, input all the gene values accurately, as shown in the image. We have to input all the two sets of
**treated**and**control**gene values of**House Keeping Gene (HKG)**and**Gene of Interest (GOI)**. Both gene sets are denoted**Ct-1**and**Ct-2**respectively.

- First, we will complete all the calculations for the
**House Keeping Gene (HKG)**section. - Now, we will take the mean value of both sets. For that, we are going to use
**the AVERAGE function****.** - Write down the following formula in cell
**E6**.

`=AVERAGE(C6:D6)`

- Press
**Enter**.

- Then,
**double-click**on the**Fill Handle**icon to copy the formula up to cell**E11**.

- After that, we have to estimate the average of the
**three**control values. - For that, write down the following formula in the merged
**F6**

`=AVERAGE(E9:E11)`

- Press the
**Enter**.

- Now, select cell
**G6**and write down the following formula to get the value of**∆Ct**. Make sure you input the**Absolute Cell Reference**for cell**F6**.

`=E6-$F$6`

- Again, press the
**Enter**.

- Then,
**double-click**on the**Fill Handle**icon to copy the formula up to cell**G11**. - Our all calculations for the
**House Keeping Gene (HKG)**are finished.

- Similarly, following the same process complete all the calculations for the
**Gene of Interest (GOI)**section.

- Finally, in cell
**O6**, write down the following formula to get the value of the expression ratio. Ensure the**Absolute Cell Reference**for cells**N6**and**H6**.

`=($N$6^M6)/($H$6^G6)`

- Press
**Enter**for the last time.

- Now,
**double-click**on the**Fill Handle**icon to copy the formula up to cell**O11**. - You will get the values of the expression ratio for every sample.

So, we can say that our method worked successfully, and we are able to analyze **qPCR** data in Excel.

## Conclusion

That’s the end of this article. I hope that this article will be helpful for you and you will be able to analyze **qPCR** data in Excel. Please share any further queries or recommendations with us in the comments section below if you have any further questions or recommendations.

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