NormFinder is another tool (an Excel add-in) to validate candidate reference genes. It best works with MS Office 2003 and up. Like GeNorm, the user has to convert the raw Cq values to relative quantities by using the ∆ct equation as shown in the last post on GeNorm. I have used NormFinder with MS Office 2003 on Windows 10 system. NormFinder can also be used with R, but I haven’t tried it yet.
Once the data is prepared i.e. raw Cq values have been converted to relative quantities, follow the steps mentioned below:
- Once you have calculated the relative amounts, arrange your data like this. The reference genes should be in columns, and the samples (including the control(s)) should be in rows. Here 1,2,3…. are the sample names while A, B, C…. are the gene names. Don’t forget to add “group” at the end. Grouping enables to show stable reference genes in groups. Here I have two different time points i.e. 1-5 samples are from the 1st time point, and 6-10 are from the 2nd time point. We will come to it in the next steps.
- Now you are ready to start NormFinder. Once you double-click the add-in file (downloaded from the site), it should show in the menu bar.
3. A short disclaimer message will show up. Just click Ok.
4. Select the input data just by dragging all the cells including the group.
5. Check all the boxes – Sample name, gene name and group identifiers. If you don’t include the group identifiers, then uncheck it. But as I suggested earlier, it would be useful to have the group identifiers.
6. Click on Go and within a few milliseconds it will create a new tab and would show the results like this:
7. If you uncheck simple output only, then it will show a detailed result page which includes stable genes, Intra- and inter- group variations. But if you check simple output only it will show only the ranking of stable genes and the most stable genes. The advantage of using group identifier is that it gives a combination of two best genes which can be used. For example, in the above case, we can use only gene A or we can use both gene A and J as the most stable gene combination.
1. Normalization of Real-Time Quantitative Reverse Transcription-PCR Data. A Model-Based Variance Estimation Approach to Identify Genes Suited for Normalization, Applied to Bladder and Colon Cancer Data Sets. 2004, Andersen CL et al.
2. NormFinder Documentation.
3. NormFinder plugin: http://moma.dk/normfinder-software. – Check the download section on the right-hand side.