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UseCase 1: qPCR with multiple reference genes​

You have multiple reference genes (usually 2 or 3) and their corresponding raw CT values. Here is how you can optimally aggregate them into one new internal control using weighted geometric mean:

Step 1: Prepare Data
The CT values can be provided in one of these three formats: 

      Sample1  Sample2 Sample3 Sample4 Sample5 Sample6 Sample7 Sample8 Sample9 Sample10 Sample11 Sample12
RNU44 25.8800  24.338  24.666  24.224 23.7500  24.642  23.720 23.2620  24.318   23.624   24.930   24.104
RNU48 21.3680  21.756  23.174  22.252 21.7820  22.994  21.564 20.9600  21.886   22.890   23.618   22.060
RNU6B 32.2575  29.480  30.455  29.765 29.7175  30.015  29.735 29.5475  30.640   30.545   30.755   30.335
 Sample1Sample2Sample3Sample4Sample5Sample6Sample7Sample8Sample9Sample10Sample11Sample12
RNU4425.8824.33824.66624.22423.7524.64223.7223.26224.31823.62424.9324.104
RNU4821.36821.75623.17422.25221.78222.99421.56420.9621.88622.8923.61822.06
RNU6B32.257529.4830.45529.76529.717530.01529.73529.547530.6430.54530.75530.335
,Sample1,Sample2,Sample3,Sample4,Sample5,Sample6,Sample7,Sample8,Sample9,Sample10,Sample11,Sample12
RNU44,25.88,24.338,24.666,24.224,23.75,24.642,23.72,23.262,24.318,23.624,24.93,24.104
RNU48,21.368,21.756,23.174,22.252,21.782,22.994,21.564,20.96,21.886,22.89,23.618,22.06
RNU6B,32.2575,29.48,30.455,29.765,29.7175,30.015,29.735,29.5475,30.64,30.545,30.755,30.335

Step 2: Upload Data
Go to app.interopt.ir. On the left panel in the Data section, set Datasets as Uploaded dataset. Then Click on the Browse button and select your CT values file. If your data only contains reference genes or low variation genes you should enable the checkbox in the Data tab.

Step 3: Choose normalization method
In Experiment setting tab choose the normalization method based on the following suggestions:

  • If your data contains less than 4 reference genes, select None.
  • If your data contains 4 or more low variation reference genes, select mean_all (average of all genes is used for normalization).
  • If your data is from a qPCR array experiment with lots of genes, select high_exp (in each sample only CT values less than 35 are used for normalization).

Step 4: Run and Collect Results
leave other options on default mode and click on Run Experiment. After the process is finished, on the right panel two tables are generated:

  • the Weighting Result shows the weights and stability measures of each combination of the reference genes.
  • the Aggregated Genes shows the aggregated reference genes after applying the weighted mean.

To download each of these tables in csv or excel format, click on the Download button at the left bottom corner of the tables. The rows in Aggreagated Genes table can be used as as artificial reference gene in delta delta ct method.

UseCase 2: Selecting best weighted combination of reference genes​

The goal here is to find the best combination of reference genes from a set. For this case you should provide one of the following data with samples from your target biological condition.

  1. CT values from a qPCR array of large number of genes
  2. CT values of 4 or more reference genes

The steps are exactly like previous section. After the processing is finished you can sort the Weighting Result table by clicking on the SD column to see the most stable combinations (with the lowest SD).