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Sample A: Cover Page of Thesis, Project, or Dissertation Proposal

Sample A: Cover Page of Thesis, Project, or Dissertation Proposal

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Figure 2.1: Batch images. Image representation <strong>of</strong> aggregated probe intensities per batch preparation. The<br />

red circle depicts a localized feature, most distinct in Batch 10. Left 4 images: raw analysis <strong>of</strong> samples<br />

meeting our filtering criteria. Right 4 images: the same samples with their cleansed probes averaged by<br />

batch preparation and only common probes allowed. Probes affected by technical variation are eliminated<br />

globally across all batches, including the ~5,600 from Batch 10.<br />

Filter Effects<br />

Since some <strong>of</strong> the filters lead to a considerable loss <strong>of</strong> the usable measurement pool, an obvious<br />

question is the imp<strong>or</strong>tance <strong>of</strong> any <strong>or</strong> all <strong>of</strong> the filters. Previously published w<strong>or</strong>k has shown the<br />

effect that SNPs can have [11]. The largest subset <strong>of</strong> data is lost from the cross-hybridization<br />

filter. It is unclear whether these potential probe-target duplexes f<strong>or</strong>m, and how much variation<br />

can be expected across a sample population. To investigate this fact<strong>or</strong>, an inversion <strong>of</strong> the cross-<br />

hybridization selection query was perf<strong>or</strong>med, which produces a set <strong>of</strong> probes all <strong>of</strong> which may<br />

cross-hybridize. If these probes are then subjected to all <strong>of</strong> the other filters we can isolate the<br />

impact <strong>of</strong> this fact<strong>or</strong>. Examples <strong>of</strong> the results are presented in Figure 2.2, showing how variable<br />

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