Hey, so at the section where you're subtracting the delta CT and you had to paste the number multiple times, instead what you can do it use the $ sign, which makes that cell value constant when you click and drag. so it look like your value is in J14, so if in K2 you did J2-$J14 then as you drag down it will keep J14 constant, if you are going to be dragging sideways you put the $ on the number instead (e.g J$14) or if you are dragging both down and sideays it would be $J$14, then that cell reference stays constant
Nivedita GAPDH is reference gene whose expression generally do not change upon treatment. The control in the given example is a huh7 cell line . In general, experimental control is the sample which has not undergone any treatment.
great video. Congratulations. I just don't understand why use the lowest value of the control to make the fold change. Wouldn’t it be ideal to use the control group average?
Hey gentleman! I really liked your video it's much helpful. I just want to know what if there are no biological Replicates? one sample with two dilutions is processed, is it fine? I will be waiting for your Reply.
If there are no biological replicates, you can also use technical replicates. and do the analysis. For statistical reasons, it is better to include biological replicates.
Thank you for the insightful video, i have a question what if I want to calculate the absolute abundance of total bacteria from my sample, could you please explain it to me?
Thank you so much for sharing this video. I have some questions about my data. If an outlier appears after the process of 2^-delta delta CT, can i delete it or use statistical method to process it? I am not sure, since if the outlier comes from my control group, it would change everything. Thanks again for this video.
Dear Viewer, To ensure the validity of our observations and to minimize the likelihood of an outlier being an actual biological phenomenon, it is advisable to include multiple replicates in our experiments. Even with the inclusion of replicates, should we still identify an outlier, we have the option to either exclude or retain this data point for subsequent statistical analysis. Therefore, by incorporating four replicates, we have the flexibility to retain three replicates while potentially discarding the fourth if it is identified as an outlier.
@@BiologyLectures Thank you so much for answering! If I set four replicates per sample, still the result is abnormal. After using static method to prove this sample’s data as an outlier, i could discard it, right?
Hi Judith, It does not matter if gene of interest is expressed more or less than the housekeeping gene. We still follow the exact same method described in the video for the calculation.
thanks for the helpful video, i have questions . i just found Cq in my results which are same to Ct. so you mean CT 1 and CT2 are like duplicate or what. i triplicate my samples (mice samples) so when i followed your videos i considered ct1, ct2, ct3 for one mice and i calculated the average. and one group contain 4 mices. is my analysis right or what
Your analysis seems correct. But if you want to calculate fold change for a group, please include the average fold change of that particular group. For example, if you have 4 mice, calculate the average fold change for 4 mice in that group.
Thank you for the video. It is very helpful for me.However, I have some questions about the experiment design. Were the three biological replicates done in one experiment or in three independent experiments? I’m designing a siRNA-knockdown experiment to test whether the expression level of the target gene is affected by the knockout gene. How do I design the biological replicates? Is it right to transfect the same siRNA into the same cells in three wells ? Best wishes.
If you are using primary cells, you can use the cells from three different donors to make three biological replicates. However, if you are using cell lines such as Hela cells, then I would suggest to do three independent experiments. If you use cells in three wells in a plate, that will be technical replicates not biological replicates.
@@BiologyLectures Sorry, I have a new question about data analysis in the case of doing three independent experiments. Is it necessary to aggregate the data from three experiments? However, this increases the error. Because qRT-PCR is too sensitive, data from three independent experiments may be consistent in trends but vary greatly in the original data. What is the correct way to analyze the data?
@@shiyuren To perform statistical analysis, I would suggest you include data from three independent experiments. Let's say that you performed three independent experiments. And for any gene for a sample let's say A. You will have one value from experiment one, one value from experiment two, and one from experiment three. While doing the data analysis, please use these values and do the calculation. Hope this helps.
Hello! Thanks for your tutorial. It is very helpful. However, I have a question in fold change calculation. I did not get why you used the smallest 2 Delta Delta ct value from the control group. As we can see from the video all 2-delta delta ct values are divided by he smallest 2 Delta Delta ct value from the control group. Could you explain it or attach reference, please? looking forward to your answer. Thanks
Dear Zhanargul, you can use any one of the three values from 2 delta delta Ct value from the control group to calculate the fold change. Generally, when we plot the graph, the average of three values of fold change for control group is made around one by multiplying or dividing by suitable factor for both control and treatmnent groups.
Please let me know one thing, You mentioned three controls mean a triplicate experiment on the same marker gene but how to get CT1 and CT2 values? I get only three Cq values of each of the target genes (triplicate experiment).
Lets say that you have 3 samples each for experimental and control condition. For each condition, you can have two technical replicates for each sample so that you will have two Ct values, CT1 and CT2 for each sample.
@@BiologyLectures Thank you for your response. Actually, I have one normal group, another one is a positive control group, and another one is the treatment group. so, when I did RT-PCR (triplicate), I got 3 CT values for each group, while you have 3 control groups, but how will I calculate the delta delta CT value?
I need to do this for my dissertation and when i calculate the fold change with a negative delta delta ct value i get an abnormally high value. Does anyone know why that is? I did this calculation exactly like in this video. So for example one of my delta delta ct values is -2. So i am basically writing down 2^-(-2).
Sorry, in this video are HepG2-1, HepG2-2 and HepG2-3 biological replicates?, Same with hu7-1, hu7-2 and hu7-3? I see you got technical replicates but do you have biological replicates? thank you!!!!!
These are technical replicates not biological replicates. Three wells from a plate in an experiment for a cell type are technical replicates not biological replicates.
i have a problem , ΔΔCT is with minus , and the CT of the housekeeping gene is lesser than the gene of interest, and the fold of change results are huge numbers like 70.000 and 300.000, i don't know where is the problem exactly? i did the calculation right , i'm really confused, can you give your email or help me, thanks in advance
The link for how to analyze qPCR data and make different types of Graph using GraphPad prism is below.:
th-cam.com/video/MlG9biZLCjw/w-d-xo.html
Hey, so at the section where you're subtracting the delta CT and you had to paste the number multiple times, instead what you can do it use the $ sign, which makes that cell value constant when you click and drag. so it look like your value is in J14, so if in K2 you did J2-$J14 then as you drag down it will keep J14 constant, if you are going to be dragging sideways you put the $ on the number instead (e.g J$14) or if you are dragging both down and sideays it would be $J$14, then that cell reference stays constant
Really informative and helpful
You are welcome
Alot of thanks for your tutorial it was very informative for me 🌹🌹🌹🌹
You are most welcome 😊
Dear Sir, please how did you get the CT2 values
Wow really helpful Video
Glad it was helpful!
helpful video
Glad it helped
It is a helpful video that I was really looking for on youtube.
Thank you. And good luck with your experiments
thank you very much a very informative video.
You are welcome
Excellent work sir
Thank you! Cheers!
easy to understand video thanks
Glad it helped
really helpful video. congratulations! ❤
Thank you very much. We are happy to hear that it helped. 🙏
Really helpful video! Thanks a lot!
I have a question: How to do the calculation when you are using target genes with zero expression in your control?
What is the logic of taking the smallest value of triplicate in the control to do relative fold change, could you explain? thanks a lot
Very helpful explanation. Thanks
Glad it was helpful!
Hello sir can i follow the same method for checking the expression of 19 genes
this tutorial it was very informative for me thank you so much
You are most welcome 🤗
Thank you!!!
You are most welcome
Why didn't you calculate the mean of 2-deltadelta CT for the control samples and used it to calculate the fold changes?
Please watch carefully. What you said has been clearly incorporated in the video.
Thank you very much for the methodological and clear explanation
You are welcome!
Thank you sir it was very helpful.. Sir while calculating avg delta ct of control why u considered first three replicates, GAPDH is the control sir,
Nivedita GAPDH is reference gene whose expression generally do not change upon treatment. The control in the given example is a huh7 cell line . In general, experimental control is the sample which has not undergone any treatment.
Okay thank you sir..sir why you considered HepG2-1 cell line GAPDH for control while calculating Delta delta ct..@@BiologyLectures
how do you separate Ct1 and Ct2 from the ct original value?
great video. Congratulations. I just don't understand why use the lowest value of the control to make the fold change. Wouldn’t it be ideal to use the control group average?
Thanks
Hey gentleman! I really liked your video it's much helpful. I just want to know what if there are no biological Replicates? one sample with two dilutions is processed, is it fine? I will be waiting for your Reply.
If there are no biological replicates, you can also use technical replicates. and do the analysis. For statistical reasons, it is better to include biological replicates.
@@BiologyLectures Thank you so much. I want to ask more about it can i have your email or contact numbe r? it would be very greatful !
@@BiologyLectures on thank, I didn't understand because you called technical replicate to your biological replicats I guess
Very good explanation 😊 can you please make a video on how to analyze data for qrtpcr with taqman.
Thank you so much.
Dear Amani,
Thank you very much. The same method can also be used to analyze data for qrtpct with raqman probes
Thank you for the insightful video, i have a question what if I want to calculate the absolute abundance of total bacteria from my sample, could you please explain it to me?
Thank you so much for sharing this video. I have some questions about my data. If an outlier appears after the process of 2^-delta delta CT, can i delete it or use statistical method to process it? I am not sure, since if the outlier comes from my control group, it would change everything. Thanks again for this video.
Dear Viewer, To ensure the validity of our observations and to minimize the likelihood of an outlier being an actual biological phenomenon, it is advisable to include multiple replicates in our experiments. Even with the inclusion of replicates, should we still identify an outlier, we have the option to either exclude or retain this data point for subsequent statistical analysis. Therefore, by incorporating four replicates, we have the flexibility to retain three replicates while potentially discarding the fourth if it is identified as an outlier.
@@BiologyLectures Thank you so much for answering! If I set four replicates per sample, still the result is abnormal. After using static method to prove this sample’s data as an outlier, i could discard it, right?
Hello nice tutorial. I have oe question, what happens when the gen of interes is expressed more than the housekepping gene?. Thanks
Hi Judith,
It does not matter if gene of interest is expressed more or less than the housekeeping gene. We still follow the exact same method described in the video for the calculation.
@@BiologyLectures and what if if the CT of my gene of interest is smaller than CT of housekeeping is that normal?
helpful video, you just need more practice with excel :)
You are most welcome.
thanks for the helpful video, i have questions . i just found Cq in my results which are same to Ct. so you mean CT 1 and CT2 are like duplicate or what. i triplicate my samples (mice samples) so when i followed your videos i considered ct1, ct2, ct3 for one mice and i calculated the average. and one group contain 4 mices. is my analysis right or what
Your analysis seems correct. But if you want to calculate fold change for a group, please include the average fold change of that particular group. For example, if you have 4 mice, calculate the average fold change for 4 mice in that group.
@@BiologyLectures please how to calculate it as you divided each value by smallest one
. thanks for your respond
Thank you for the video. It is very helpful for me.However, I have some questions about the experiment design.
Were the three biological replicates done in one experiment or in three independent experiments?
I’m designing a siRNA-knockdown experiment to test whether the expression level of the target gene is affected by the knockout gene. How do I design the biological replicates? Is it right to transfect the same siRNA into the same cells in three wells ?
Best wishes.
If you are using primary cells, you can use the cells from three different donors to make three biological replicates. However, if you are using cell lines such as Hela cells, then I would suggest to do three independent experiments. If you use cells in three wells in a plate, that will be technical replicates not biological replicates.
@@BiologyLectures Thank you for your help! You are one of my favorite teachers.
@@BiologyLectures Sorry, I have a new question about data analysis in the case of doing three independent experiments. Is it necessary to aggregate the data from three experiments? However, this increases the error. Because qRT-PCR is too sensitive, data from three independent experiments may be consistent in trends but vary greatly in the original data. What is the correct way to analyze the data?
@@shiyuren To perform statistical analysis, I would suggest you include data from three independent experiments. Let's say that you performed three independent experiments. And for any gene for a sample let's say A. You will have one value from experiment one, one value from experiment two, and one from experiment three. While doing the data analysis, please use these values and do the calculation. Hope this helps.
Hello! Thanks for your tutorial. It is very helpful. However, I have a question in fold change calculation. I did not get why you used the smallest 2 Delta Delta ct value from the control group. As we can see from the video all 2-delta delta ct values are divided by he smallest 2 Delta Delta ct value from the control group. Could you explain it or attach reference, please? looking forward to your answer. Thanks
Dear Zhanargul,
you can use any one of the three values from 2 delta delta Ct value from the control group to calculate the fold change. Generally, when we plot the graph, the average of three values of fold change for control group is made around one by multiplying or dividing by suitable factor for both control and treatmnent groups.
Please let me know one thing, You mentioned three controls mean a triplicate experiment on the same marker gene but how to get CT1 and CT2 values?
I get only three Cq values of each of the target genes (triplicate experiment).
Lets say that you have 3 samples each for experimental and control condition. For each condition, you can have two technical replicates for each sample so that you will have two Ct values, CT1 and CT2 for each sample.
@@BiologyLectures
Thank you for your response.
Actually, I have one normal group, another one is a positive control group, and another one is the treatment group. so, when I did RT-PCR (triplicate), I got 3 CT values for each group, while you have 3 control groups, but how will I calculate the delta delta CT value?
Those three replicates are biological replicates but ct1 and ct2 are technical replicates
I need to do this for my dissertation and when i calculate the fold change with a negative delta delta ct value i get an abnormally high value. Does anyone know why that is? I did this calculation exactly like in this video. So for example one of my delta delta ct values is -2. So i am basically writing down 2^-(-2).
Yes that is absolutely correct. This means that you have very high expression of your candidate gene.
Sorry, in this video are HepG2-1, HepG2-2 and HepG2-3 biological replicates?, Same with hu7-1, hu7-2 and hu7-3? I see you got technical replicates but do you have biological replicates? thank you!!!!!
These are technical replicates not biological replicates. Three wells from a plate in an experiment for a cell type are technical replicates not biological replicates.
For Relative fold change, if I take the average of control (HepG2) and that average use to divide other groups, it would not be a fold change....?
the same question as mine
I was bit confused as I was not in touch with this since 2yrs...after watching this it's too clumpsy
Please watch multiple times by pausing the video. Hopefully you will be able to understand the calculation. All the best
bro do you even excel lol
😊
Kwana de
i have a problem , ΔΔCT is with minus , and the CT of the housekeeping gene is lesser than the gene of interest, and the fold of change results are huge numbers like 70.000 and 300.000, i don't know where is the problem exactly? i did the calculation right , i'm really confused, can you give your email or help me, thanks in advance
I am having similar problem...did u get this clarified?