Hello dear community,
we recently submitted an experiment with multiple celllines, control vs. treatment, 3 biological replicates per condition per cellline for expression profiling using Illumina HT-12 microarrays.
In the original run, we tried to counter batch effects by blocking and randomization. Unfortunately, one of the samples was not processed correctly and was recently re-run as a "filler" sample on an unrelated project.
Now while the QC on this run looks ok on the probe level (hybridization, housekeeping genes), the sample does not really fit in with its peers (please ignore HN038M). The sample in question in the dendrogram below is "Caski T 2".
The question is now what one can do with such an outlier? Should we just go on with analysis? Are there recommendations for downweighting such cases in limma? Should we omit this sample alltogether - it would be 3 controls vs. 2 treatment samples then? Or worse, should we re-run the entire six samples for this cellline?
I really appreciate any input on this - thank you very much in advance!
Simon
The QC generated with arrayQualityMetrics for the summarized set before normalization is here, including PCA plot and boxplots (non-normalized, looks ok as well after normalization):
QC report
As for the different dendrograms - I'll check tomorrow!
@Kevin Blighe: Thank you very much for your input! :-)