Thank you so much for your warm words and blessings! It truly means a lot to me. I'm glad to have such supportive and kind-hearted viewers. Wishing you all the best!
Hi! Thanks for your comment. I currently don't use Quad Studio 7 Pro, but importing a plate map usually follows a similar process in most software. You typically need to format your plate map in a compatible spreadsheet format (like Excel or CSV), ensuring the wells are correctly labeled. Then, look for an option within the software to import the file under the 'Plate Setup' or 'Layout' tab. If I come across any specific steps for Quad Studio 7 Pro, I’ll share them. Meanwhile, I suggest checking the user manual or support forums for more detailed guidance. Hope this helps!
steps: 1. Create Your Plate Map: Prepare your plate layout in a spreadsheet (Excel or CSV format), ensuring each well is labeled with the appropriate sample, control, or blank. 2. Find the Import Option: In Quad Studio 7 Pro, look for the 'Plate Setup' or 'Layout' section. There should be an option to import your plate map. It might be under 'File' or 'Import Plate Layout.' 3. Select Your File: Choose the file you created and follow any prompts to map the wells correctly. I recommend checking the software manual or help section for detailed steps tailored to Quad Studio 7 Pro. Hope this helps! Feel free to reach out if you have more questions.
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 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!
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!
sir may i ask you, if i have a sample of group A dan B, for ddCt A is use dCt-average of dCT A, and for ddCt B is use dCt-average dCt B , is that right sir..? this is for looking the different expression gen from group A and group B.. thankyou in advance sir..
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..
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
Hello, I want to ask you something. In my experimetn, I want to compare the difference of gene expresison of some key genes after sample treatments with DMSO (considered as control), compound A at 50ug and compound A at 100ug/mL. So, it means for reference gene (GAPDH) and target genes I will have all three conditions of DMSO, compound treated at 50ug/mL and compound treated 100ug/mL. In my case, how can I calculate ∆CT and ∆∆CT?
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
Sir, so to get average and sd se values, i need to perform multiple qpcr? As for each qpcr, i am getting one del del cT value for control and one for the treated sample. Great video sir by the way
How to select treatment groups in Plant extract experements, where one is standard group,other disease and extract groups as dose dependent groups, kindly explain
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.
nice explanation. I am trying real-time PCR with TaqMan probe with the manual master mix but I am not getting a curve graph for amplification curve. Can you explain real-time PCR with TaqMan probe (cy5)?
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 th-cam.com/video/fkUDu042xic/w-d-xo.html
Thanks Shashi, excellent video. I have a question, is it necessary to have an endogenous control for each sample on the plate or can I have only one duplicate of endogenous control for all my duplicates of the same treatment? For example, one endogenous control duplicate for all my Treatment 1 samples, another endogenous control duplicate for all my samples from Treatment 2, and so on...
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.
could you also present elisa data. analysis like 4-parameters equation to find protein concentration? thank you advance. can i get this data sample for us to practice?
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 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
Hello thank for the very informative video ❤ can you please explain how we can interpret the data afterwards like if the fold change increased how does that apply to the gene
hi there, thank you for the great video. how would you go about doing this if you do not have control vs treated, instead you just want to compare genes of interest and housekeeping genes of different genotypes? Thanks!
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
Nice video. I have questions and clarification; what if I did not run my samples in duplicate or triplicate but singly? what is the essence of this fold change calculation? And what do you mean by endogenous control group?
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.
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 th-cam.com/video/u_BIi1LzhsI/w-d-xo.html
I am really struggling with the calculation for qPCR, which is my final year project. I have two genes and 1 housekeeping gene. And for each give I have 1 control and 3 different treatments. I took the average of triplicates and d-CT. But I don't know how to do ddct.
To calculate the relative gene expression using the ΔΔCt (delta-delta Ct) method in qPCR, follow these steps: Key Components: 1. Ct values: The cycle threshold values from the qPCR data. 2. Housekeeping gene: Used to normalize the expression of target genes. 3. ΔCt (delta Ct): Normalization against the housekeeping gene. ΔCt=Ct target − Ct housekeeping 4. ΔΔCt (delta-delta Ct): Comparison to the control sample. ΔΔCt=ΔCt treatmen t− Δct control
5. Fold change in expression:
Fold change=2−ΔΔCt Example Process: 1. Average the triplicates: Compute the mean Ct values for each gene (target and housekeeping) from the triplicate qPCR runs. 2. Calculate ΔCt: For each sample: ΔCt=Mean Cttarget−Mean Cthousekeeping 3. Choose your control sample: Use the control group to calculate the baseline ΔCt: ΔCt control= Mean Ct target−Mean Ct housekeeping 4. Calculate ΔΔCt: For each treatment: ΔΔCt=ΔCttreatment−Δctcontrol 5. Determine fold change: For each treatment, use: Fold change=2−ΔΔCt Please let me know if this was useful.
GraphPad Prism is a commercial software, and the full version is not available for free. However, you can download a free trial version directly from the official GraphPad website. The trial typically lasts 30 days and provides access to all features, allowing you to evaluate the software before purchasing.
Very innovative
Thank you Sir
For your appreciation
beautiful explaination
Thank You
Thank you! This is absolutely what I wanted to know!
Glad it was helpful!
Thankyou soo much for such a informative video sir..
Thanks for appreciation
Well explained and informative...
Glad to found you on TH-cam
very nice
superb .. nice teaching
Excellent video, made my work so easier, thank you!
You are a grt teacher....🙏
Thank you 🙏
That's a lot of motivation for making more tutorials
@@LearnInnovativelywithMe you are most welcome 🙏
Thank you. Great help.
You're welcome!
VERY INFORMATIVE AND EASY TO FOLLOW
Glad it was helpful!
Thank you so much, very informative video! Saved me from hours of confusion and mislead!
Thank you very much for the video and especially for sharing the data
Nicely, simply, and efficiently explained, very good video, Sir.
Nicely explained
Is it possible to see pesonally and solve the problem occurred in my project work. thanks.
You are really good 🤘
Thanks a lot!
thank you, sir. very helpful
Glad it helped
Really helpful. Thanks
Glad to hear that!
Excellent
Thanks dear
God bless you. Thank you
Thank you so much for your warm words and blessings! It truly means a lot to me. I'm glad to have such supportive and kind-hearted viewers. Wishing you all the best!
Thank you so much
Thanks ❤
In these tests the treatment group and the control group are independent from each other correct?!
Yes, in these tests, the treatment group and the control group are indeed independent from each other.
Hi Sir, Do you use Quad Studio 7 Pro?if so, please can you let me know how to import a plate map ?
Hi! Thanks for your comment. I currently don't use Quad Studio 7 Pro, but importing a plate map usually follows a similar process in most software. You typically need to format your plate map in a compatible spreadsheet format (like Excel or CSV), ensuring the wells are correctly labeled. Then, look for an option within the software to import the file under the 'Plate Setup' or 'Layout' tab.
If I come across any specific steps for Quad Studio 7 Pro, I’ll share them. Meanwhile, I suggest checking the user manual or support forums for more detailed guidance. Hope this helps!
steps:
1. Create Your Plate Map: Prepare your plate layout in a spreadsheet (Excel or CSV format), ensuring each well is labeled with the appropriate sample, control, or blank.
2. Find the Import Option: In Quad Studio 7 Pro, look for the 'Plate Setup' or 'Layout' section. There should be an option to import your plate map. It might be under 'File' or 'Import Plate Layout.'
3. Select Your File: Choose the file you created and follow any prompts to map the wells correctly.
I recommend checking the software manual or help section for detailed steps tailored to Quad Studio 7 Pro. Hope this helps! Feel free to reach out if you have more questions.
Very useful. Thank you very much!
Glad it was helpful!
Thank you so much for these informative video!! It makes everything clear for me! Please keep share with us this kind of valuable information.
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 it was really really GOOD and informative ..KEEP DOING IT SIR
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!
thank you so much, it's very clear
Sir what about negative control....in qpcr only positive control is used?
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!
Thank you! You got new subscriber, sir!
Awesome, thank you!
sir may i ask you, if i have a sample of group A dan B, for ddCt A is use dCt-average of dCT A, and for ddCt B is use dCt-average dCt B , is that right sir..? this is for looking the different expression gen from group A and group B.. thankyou in advance sir..
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..
Hi sir, Great video., Thank you very much
thank you
Dear, If I have two endogenous control then how can I do calculations? please
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
Which software it is???
Thank you very much for this sir
Your new subscriber from Pakistan residing in China
Thank you 😊
@@LearnInnovativelywithMe welcome
Hello, I want to ask you something. In my experimetn, I want to compare the difference of gene expresison of some key genes after sample treatments with DMSO (considered as control), compound A at 50ug and compound A at 100ug/mL. So, it means for reference gene (GAPDH) and target genes I will have all three conditions of DMSO, compound treated at 50ug/mL and compound treated 100ug/mL. In my case, how can I calculate ∆CT and ∆∆CT?
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
Sir, so to get average and sd se values, i need to perform multiple qpcr? As for each qpcr, i am getting one del del cT value for control and one for the treated sample. Great video sir by the way
How to select treatment groups in Plant extract experements, where one is standard group,other disease and extract groups as dose dependent groups, kindly explain
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.
nice explanation. I am trying real-time PCR with TaqMan probe with the manual master mix but I am not getting a curve graph for amplification curve. Can you explain real-time PCR with TaqMan probe (cy5)?
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
th-cam.com/video/fkUDu042xic/w-d-xo.html
Thanks Shashi, excellent video. I have a question, is it necessary to have an endogenous control for each sample on the plate or can I have only one duplicate of endogenous control for all my duplicates of the same treatment? For example, one endogenous control duplicate for all my Treatment 1 samples, another endogenous control duplicate for all my samples from Treatment 2, and so on...
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.
could you also present elisa data. analysis like 4-parameters equation to find protein concentration? thank you advance. can i get this data sample for us to practice?
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
Sir, can you please explain how we can make bar plots and from which values we can make it...?
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.
Nice video, how can i perform the calculation if my gene of interest is more expressed than my housekeeping gene? Thanks
Hello thank for the very informative video ❤ can you please explain how we can interpret the data afterwards like if the fold change increased how does that apply to the gene
hi there, thank you for the great video. how would you go about doing this if you do not have control vs treated, instead you just want to compare genes of interest and housekeeping genes of different genotypes? Thanks!
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
Hi sir
Do you have an video how to normalize the target using expression of reference gene
Hi
Sorry for the delayed response
I don't think so but I will prepare in future.
Thank you
Hi Sashi, how did you calculated SD?
th-cam.com/video/xioBD99CyvI/w-d-xo.html
How can I use real time pcr pioneer
Sir subtitles ke wajase we can't see graphs...
Dear Sir, Can you please provide some paper references regarding this calculation.
So i can mentioned it in a paper
Nice video.
I have questions and clarification; what if I did not run my samples in duplicate or triplicate but singly?
what is the essence of this fold change calculation?
And what do you mean by endogenous control group?
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.
How to analyse Quantitative Data analysis...????
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
th-cam.com/video/u_BIi1LzhsI/w-d-xo.html
Great video... can you please share the excel worksheet draft of this ?
th-cam.com/users/redirect?event=comments&redir_token=QUFFLUhqbUxEaUN1c2FYTGdPdkVaRm9GTDk4WXVTNzVtZ3xBQ3Jtc0tuN0Yzd3pQNVdfd0U0SExYQ0c5OTU5TzVTb1JJdnFVa3ByUXBXNnVRUloxMThmcWh2eE1rdDZYMENNSWV4N2VJc2ZjRWIwUEw4c2N5Rjcyc2NpaHRkQmRvNWVpTUNmTEZPMDRyOTJpcDZidzg3bnhFVQ&q=https%3A%2F%2Fdocs.google.com%2Fspreadsheets%2Fd%2F1iEFVzSqPLdqd0nEGjTvdbbjCos6LWGz3%2Fedit%3Fusp%3Dsharing%26ouid%3D118038295575398446904%26rtpof%3Dtrue%26sd%3Dtrue&stzid=Ugyw8boZpMsOMlw34JN4AaABAg.9p-YA4tp7P19qB4gzognQr
@@LearnInnovativelywithMe Thanks alot 👍👍
Dada ki kolkata theke?
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
I am really struggling with the calculation for qPCR, which is my final year project. I have two genes and 1 housekeeping gene. And for each give I have 1 control and 3 different treatments. I took the average of triplicates and d-CT. But I don't know how to do ddct.
To calculate the relative gene expression using the ΔΔCt (delta-delta Ct) method in qPCR, follow these steps:
Key Components:
1. Ct values: The cycle threshold values from the qPCR data.
2. Housekeeping gene: Used to normalize the expression of target genes.
3. ΔCt (delta Ct): Normalization against the housekeeping gene.
ΔCt=Ct target − Ct housekeeping
4. ΔΔCt (delta-delta Ct): Comparison to the control sample.
ΔΔCt=ΔCt treatmen t− Δct control
5. Fold change in expression:
Fold change=2−ΔΔCt
Example Process:
1. Average the triplicates:
Compute the mean Ct values for each gene (target and housekeeping) from the triplicate qPCR runs.
2. Calculate ΔCt:
For each sample:
ΔCt=Mean Cttarget−Mean Cthousekeeping
3. Choose your control sample:
Use the control group to calculate the baseline ΔCt:
ΔCt control= Mean Ct target−Mean Ct housekeeping
4. Calculate ΔΔCt:
For each treatment:
ΔΔCt=ΔCttreatment−Δctcontrol
5. Determine fold change:
For each treatment, use:
Fold change=2−ΔΔCt
Please let me know if this was useful.
How can I download graphpad prism for free
GraphPad Prism is a commercial software, and the full version is not available for free. However, you can download a free trial version directly from the official GraphPad website. The trial typically lasts 30 days and provides access to all features, allowing you to evaluate the software before purchasing.
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