How should I detect and deal with potential outlier samples?

Potential outlier samples can be identified from PCA plots. The potential outlier will distinguish itself as the one located far away from the major clusters formed by the remaining samples.

To deal with outliers, the first thing is to check the QA/QC wells to see if there were some obvious technical problems. If they are flagged and the sample appears as an outlier in the PCA plot, the sample should be removed from the input data using the “Data Editor” dialog on the Quality Check page.