1. Quality Control Report on Roslin Samples by Leo Zeef
dChip report shows very consistent performance for the arrays with the exception of samples 12 and 7. A warning is given if the “% Array outliers” is higher than 5%. This measure is a probeset level quality control measure and is a good measure of aberrant performance of an array. The percentage present calls is also very low for these two arrays.

2. PCA analysis. Red sample are day 0 mice and blue are day 7
PCA analysis. Red sample are day 0 mice and blue are day 7. 3 mice strains are the three different icon shapes. Despite the QC problems the two outliers still cluster in the expected positions on the first component. The second component is determined by the outlier problem and the third component is separating the samples on mouse strain. This suggests the QC problem does not destroy the biological signal. pto
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3. How bad are the outliers
How bad are the outliers? Component 2 (which is revealing the outliers) is almost as strong as component 1. Component 3 trails a long way behind. The data definitely improves by removing the two outliers, but as mentioned the QC problem does not destroy the biological signal and so at a desperate push they could still be useable.
PCA details (using all the samples)
PCA without the 2 outliers
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