How to Analyze Real time PCR Data? | Real Time PCR Gene Expression Fold Change Calculation 

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You're welcome! I'm delighted that the video provided valuable information and brought clarity to your understanding. Rest assured, I will continue sharing such valuable content with you. Moreover, I would like to inform you that I have shared an Excel data file containing fold change expressions for learning purposes. Feel free to explore it and analyze the data. If you have any further questions or require additional assistance, don't hesitate to ask. Lastly, please feel free to share this video with your friends who might find this information helpful. Thank you! docs.google.com/spreadsheets/d/1iEFVzSqPLdqd0nEGjTvdbbjCos6LWGz3/edit?usp=sharing&ouid=118038295575398446904&rtpof=true&sd=true

Thank you so much! Is it the same calculation for miR expression using Taqman ?

Thank you so much for your kind words! I’m really glad to hear that you found the content informative and helpful. Your support and feedback mean a lot to me. I'll definitely keep working hard to bring more valuable content. If you have any more questions or suggestions, feel free to let me know!

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@@LearnInnovativelywithMe you are most welcome 🙏

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Please follow these step I hope this may help you But please varify the results on your basis. Good Luck Step 1: Gather Ct Values First, you'll need to obtain the Ct (threshold cycle) values for both your reference gene (GAPDH) and your target genes under each condition: DMSO (control), compound A at 50 μg/mL, and compound A at 100 μg/mL. Step 2: Calculate Δct The ΔCt value is calculated by subtracting the Ct value of the reference gene (GAPDH) from the Ct value of the target gene for each sample. ΔCt=CtTarget Gene - CtReference Gene For each condition (DMSO, 50 μg/mL, 100 μg/mL), calculate Δct as follows: • DMSO (control): ΔCTDMSO = CtTarget Gene, DMSO - CtGAPDH, DMSO • Compound A at 50 μg/mL: ΔCt50 μg/mL = CtTarget Gene, 50 μg/mL - CtGAPDH, 50 μg/mL • Compound A at 100 μg/mL: ΔCt100 μg/mL = CtTarget Gene, 100 μg/mL - CtGAPDH, 100 μg/mL Step 3: Calculate ΔΔCt The ΔΔCt value is calculated by subtracting the ΔCt value of the control (DMSO) from the ΔCt value of each treated sample. ΔΔCt=Δct Treatment - ΔCtControl For each treatment, calculate ΔΔCt as follows: - • Compound A at 50 μg/mL: ΔΔCt50 μg/mL = ΔCt50 μg/mL - ΔCTDMSO • Compound A at 100 μg/mL: AAC100 μg/mL =ΔCt100 μg/mL -ΔCtDMSO Step 4: Calculate Relative Gene Expression Finally, the relative expression level of the target gene can be calculated using the formula: Relative Expression = 2-ΔΔCt This value represents the fold change in gene expression of the treated samples compared to the control (DMSO). Example: Suppose you have the following Ct values: DMSO (control): Ct Target = 22, Ct_GAPDH = 18 Compound A at 50 μg/mL: Ct_Target = 20, Ct_GAPDH = 18 Compound A at 100 μg/mL: Ct Target = 19, Ct_GAPDH = 18 Then, calculate as follows: ΔCt for DMSO: ΔCTDMSO = 22-18=4 Δct for Compound A (50 μg/mL): ΔCt50 μg/mL=20-18=2 •ΔCt for Compound A (100 μg/mL)): ΔCt100 μg/mL = 19-18=1 ΔΔCt for 50 μg/mL: ΔΔCt50 μg/mL = 2-4=-2 ΔΔCt for 100 μg/mL: ΔΔC100 μg/mL =1-4=-3 Relative Expression for 50 μg/mL: 2-ΔΔCt-2-(-2) = 2 2 = 4 fold increase Relative Expression for 100 μg/mL: 2-ΔΔCt-2-(-3)=2 3=8 fold increase

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Certainly! In qPCR, both positive and negative controls are utilized. Specifically, for the negative control, we typically use Non-Template Controls (NTC), which consist of the master mix but exclude the template. For each gene transcript being tested, a respective NTC is included. For instance, if qPCR is being conducted for 5 different genes, there will be 5 corresponding NTCs, each for its respective master mix. This ensures accuracy and specificity in the results. Thank you for your question, and I'm glad this information can be of help to you and others!

Thanks dear

Thank you 😊

@@LearnInnovativelywithMe welcome

Yes, in these tests, the treatment group and the control group are indeed independent from each other.

Thanks I suggest you please use the TaqMan Master mix with TaqMan Probe because they provide specialized probe without Hydroxyl group Maybe the below link can help you ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-fkUDu042xic.html

Hello, I appreciate the time you've taken to engage with the tutorial. As you continue your exploration into differential gene expression between two groups, it's crucial to emphasize the role of your endogenous control (or reference gene) in this analysis. The stability of this gene's expression across your experimental conditions is pivotal. Any fluctuations in its expression could potentially skew your results. To further aid your understanding of the analysis and its application, I'm sharing the data file that was used in the tutorial. This will provide you with a practical resource to learn from and experiment with, allowing you to more effectively apply the knowledge to your own data. You can find the data file at the link provided below. Enjoy your learning journey! docs.google.com/spreadsheets/d/1iEFVzSqPLdqd0nEGjTvdbbjCos6LWGz3/edit?usp=sharing&ouid=109764848498207362601&rtpof=true&sd=true

@@LearnInnovativelywithMe thank you for the answer and the data, sir!! I really appreciate it.. but I want to ask again sir, if the 2 groups are not control and treatment, i mean 2 groups with different samples, does the ddct use the formula with an average of only 1 group? as in the tutorial for treatment using the average dct control..

Calculate fold change off all the group using Standard group with no tretment from dose as control and rest of the group as treatment Analyse your data using Two way ANNOVA. Keep your dose variable in Row and Standard as well as Disease group in column.

Thanks You can calculate the delta ct from the each individual from their respective housekeeping gene and for the relative gene expression change It is essential to consider atleast one sample or group as reference from which you can calculate the delta delta ct value and fold change expression. I hope this may help you

Thanks for your appreciation You can use one or one duplicate endogenous control for each treatment group in case of cell line or in that situation where less variation found among individuals within same group of treatment. if variation present or you are using patients sample in which variation possible I recommend you please use endogenous control for every sample of treatment group or patients. I hope this may help you

@@LearnInnovativelywithMe I actually have limited reactions available, so I can´t tell if I´ll have variation or not, I only have one chance to get good results. I am working with zebrafish liver RNA samples exposed to certain compounds. I was thinking of using an endogenous control in triplicate for each treatment groups (I have 3 samples of 6 treatments). Also, I dont know if I need a positive control in my experiment.

Hi People generally use the Standard Error value to show on the bar You can make it using microsoft excel. I will upload the tuturial about it as soon as possible Thanks

@@LearnInnovativelywithMe thankyou Soo much sir

I have uploaded the Tutorial about how we can add the error bar on graph.

May be more than that

Hello, thanks for reaching out with your questions. I'm happy to help clarify. 1. Running samples in duplicate or triplicate: Ideally, experiments should be conducted in duplicate or triplicate as this allows for the averaging of results and the determination of standard deviations, which ultimately provide a measure of data reliability. Conducting experiments once, or singly, can lead to erroneous interpretations because there might be experimental errors, anomalies, or outliers that are not accounted for. However, if you only ran your samples once, you can still interpret the data, but keep in mind that this may increase the chances of potential inaccuracies. 2. Fold change calculation: The fold change in an experiment is a measure used in bioinformatics to describe how much a quantity changes going from an initial to a final value. It's essentially a ratio that tells you the multiplier effect of the change. For example, a fold change of 2 means the quantity doubled. It is commonly used in various biological and biochemical experiments, like gene expression analyses, where it's crucial to quantify the degree of change in expression between two conditions (such as diseased vs. healthy tissue). 3. Endogenous control group: In the context of an experiment, an endogenous control, also often referred to as a "housekeeping" gene or internal control, is a selected stable gene in your sample that does not change its expression level despite experimental conditions. It is used to normalize the results of other genes of interest. This is important because it accounts for variability in the quantity or quality of your initial sample, ensuring that the changes you see are due to your experimental manipulation and not differences in sample loading, preparation, or other variables. I hope this helps! Please feel free to ask if you have any more questions or need further clarification on any points.

Hello Diana, I will make an effort to prepare the content as per your suggestion. Additionally, I am sharing the data with you and also in the comment section so that anyone can utilize it for the exercise. I hope this proves helpful to you. docs.google.com/spreadsheets/d/1iEFVzSqPLdqd0nEGjTvdbbjCos6LWGz3/edit?usp=sharing&ouid=118038295575398446904&rtpof=true&sd=true

Hi You can take average of endogenous control and then calculate delta Ct & also delta delta Ct of each respective sample or subject. I hope this normalization process will not affect your data. May be this process will enhanced the accuracy of your result.

@@LearnInnovativelywithMe Thanks for reply. But dear How can i calculate the detla Ct and Delta Delta Ct from two control. I do not understand. please share ur email address so that i can share my file with you. Thanks

@@ranakhalidiqbal1407 learninginnovatively@gmail.com

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@@LearnInnovativelywithMe Thanks alot 👍👍

Sorry for the delay For Quantitative data analysis you need to setup the qPCR experiment having standard curve You can see my video tutorial on qPCR setup ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-u_BIi1LzhsI.html

ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-xioBD99CyvI.html

I don't understand what you are saying but may be you are asking for the residance location . I belongs to the Uttar pradesh. Sorry about that

Hi Sorry for the delayed response I don't think so but I will prepare in future. Thank you