It is not possible to combine raw data or other intermediates from the data analysis from different conventional MLPA or digitalMLPA experiments into a single analysis. It is possible to combine data from two sequencing runs on the same digitalMLPA products to obtain sufficient reads for data analysis.

Background

Conventional MLPA and digitalMLPA are relative techniques. All steps in the experimental procedure can introduce variation. Therefore, test samples and reference samples must be part of the same experiment, using the same master mixes. The final probe ratios that are obtained after normalisation can be compared, as the normalisation will have removed most of the experimental variation.

In digitalMLPA experiments, it is also important that test and reference samples are part of the same sequencing run in the same flow cell to limit variability. There is only one scenario in which data from two different sequencing runs can be combined in a single analysis, and this is when the entire run is repeated to obtain more reads. In this scenario both runs can be combined, as test and reference samples have still been treated equally.