Hello Hoda. Don't worry. That in essence is what this forum is about: a dialogue to assist and clarify and help clear up any misunderstandings. So in that sense it has done its job !!

Hi Hoda

the delta delta ct analysis of qPCR data as explained in attached paper is designed to show magnitude of change in a treated sample compared to untreated control. Thus the untreated control whose expression level based on magnitude of fluorescent signal is assigned a value of 1 and the magnitude of fluorescence in the treated sample is then compared to the signal in the untreated sample in order to calculate the fold change in expression, I.e whether for example treating results in expression increasing 10 fold in the treated sample or for example goes down 10 fold as a result of treatment. As explained in the delta delta ft analysis paper if this difference is computed to be statistically significant then you have demonstrated an absolute and unequivocal relationship between treatment and expression for that gene. To reiterate for this type of trend analysis you need treated samples untreated controls and expression data in both sets of samples for a housekeeping gene line gapdh as well - which is meant not to change in either sample sets and can thus be used to calculate specific signal or signal to noise in both sample sets. See that paper for details

In contrast in certain situations you don't just need to know the relationship between treatment and expression for a particular gene but the actual number of molecules or copy number for the 2 sample sets before and after treatment.  I have provided a link to another more general data analysis paper why talks about why you would want to ascertain copy number and how you do it.  In essence this is usually based on an empirically verified standard curve for your gene of interest and your samples ; that is the relationship between actual copy number and fluorescent signal

https://www.dropbox.com/s/5ri0l1o8foc17vo/delta%20delta%20ct%20analysis.pdf?dl=0

https://www.dropbox.com/s/d4zh26drtmjc6do/qPCR%20data%20analysis_principles.pdf?dl=0

Hi Hoda

if you have trouble accessing these files I can send the actual files tomorrow or can attach to an e mail. My I phone can only really provide a link to a deposited file rather than actual file. Cheers 

@ Laurence Stuart Hall

thank you for your response i get the delta delta change Ct but what i didn't get how can i use the empirically verified standard curve for my gene of interest and how i can find the relationship between actual copy number and fluorescent signal. you can see in the attached paper in supplementary table 2 they express the level with absolute number and in table 3 did ROC curve on these level .... this is what i didn't get 

http://www.nature.com/article-assets/npg/srep/2014/140903/srep06277/extref/srep06277-s1.pdf

Hi Hoda

just had a quick look at the paper you sent me and all I can see is percent expression and fold change which is relative and not absolute (copy number)

Sorry I cannot be of more help

Best wishes

It depends on what type of miRNA qPCR strategy and data analysis tools you are using in your study. Fold change detection is pretty common. You can check this attached paper. If you need more elaborated data analysis and explanation I can send them too. I hope you will get your answer

Article Altered microRNA Expression Profiles and Regulation of INK4A...

@Laurence Stuart Hall thank you very much i now got what you explained to me in your first comment and understood the paper i attached as you explained to me that number are relative expression not absolute . thank you again you helped me sooooo much sorry for this miss understanding.

Hello Hoda. Don't worry. That in essence is what this forum is about: a dialogue to assist and clarify and help clear up any misunderstandings. So in that sense it has done its job !!