Can customers compare and combine different Explore runs with each other or with other historical Explore studies?

Comparisons between Explore projects will be handled similarly as for existing Olink Target products, that is, by using overlapping bridging samples.

The bridging samples are used to calculate an adjustment factor that is applied to adjust each assay to make the datasets comparable. The accuracy and precision in the estimate of the adjustment factor increases with more bridging samples. 8-16 bridging samples are recommended, as this gives a good balance between the error in the estimate and the number of bridging samples.

For any bridging normalization to be successful, the bridging samples need to represent the study samples well and need to be within the dynamic range of most assays.

Not what you were looking for?

Ask us