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Missing Data and Off-scale Measurements
Occasionally, an amplification response curve never reaches the threshold which generates missing data, or a melting point analysis reveals that an amplification signal is due to primer-dimer formation and not the targeted product. The corresponding Cq values will be irrelevant and must be handled. If the amplifiation response never reaches the threshold, it is called an off-scale measurement.
The experiment should be repeated if the results are due to experimental error. If there was no experimental error and several samples were taken under the same conditions, the data from the other samples can be used to fill in the gaps. Or if a series of samples were taken, it might be possible to interpolate to fill the empty cells. The suggested process to handle missing data and off-scale measurements is as follows:
Open the data in the Data editor and validate the sheet by pressing the Validate sheet button. The cells with missing data are colored pink and a report of the empty cells is presented.
Press the Missing data button in the tool bar, or select Missing data in the Pre-processing menu to open a dialog box. You can replace all missing data with one given Cq value (Fill all empty cells with _), set different Cq values for missing data in different columns (genes) (Fill the empty cells in column _ with _), or replace missing data with Their respective column mean values. If a missing data is due to an off-scale measurement, it is recommended to set this Cq value higher than any of the positive samples (Fill with column maximum +_). If there is a classification column that defines replicate samples, it can be used to fill the empty cells with The mean of replicates. There is also an alternative to fill all empty cells in one column with the values on the same rows in another column (Fill the empty cells in column _ with values from column _).
The Cq values of primer-dimer signals can vary substantially and this variation should not be considered in any analysis. Selecting Cut-off in the Pre-processing menu in the Data Editor opens a dialog box. Here you can replace all Cq values higher than a threshold value with a given value. Typically you would set them to the same Cq value as the missing data. You can also use the dialog to color cells with values higher or lower than a given value so that they can be easily found and investigated. If the check box ABS(value) is ticked, the absolute value of the data will be checked.