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As further discussed below, Raindance performance on the unmatched sample set was markedly lower than observed for the matched sample set, primarily due to an outlier sample with low (38%) on-target efficiency.
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Quality control analyses did not reveal any outlier samples.
Unsupervised hierarchical clustering by sample was performed to confirm that replicates within each condition grouped with most similarity, and to identify any outlier samples.
As shown in Fig. 7, all the nonresponders had lower values for the 4825-Da feandre and higher values for the 3276-Da and 3293-Da peaks than did the responders, with the exception of a single outlier sample.
Even a single CAG outlier sample, with a very long CAG repeat and extremely young age at onset relative to all others, can have a profound effect on the final result when testing for the effects of potential genetic modifiers (Lee et al. 2012).
Again, raindance performance is notably lower in the ummatched compared to the matched set; this is largely attributable to one outlier sample that exhibited a lower on-target efficiency.
One outlier sample turned out to be a lymphoma and was excluded from SAM analysis.
One outlier (sample Colon_Embryo_Day21_rep1) was identified (data not shown) and was eliminated from the analysis.
The three samples and another one outlier sample were excluded at the subsequent analysis.
The only outlier sample seemed to be the pineal gland of the Large White male (PING_LWM), which clustered with the rest of hypothalamus microarrays.
Here, the OS statistic [13], [15], [21] was proposed to replace the rth percentile with a sum over the outlier samples from the disease group above a given cut-off.
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