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In our case, we used the in-plate controls as training sets to remove the laborious manual classification step.
Reference-free 2D classification in IMAGIC was subsequently used on the data sets to remove averages with blurred appearance or incorrect size.
Results: We propose TileProbe, a new technique that builds upon the MAT algorithm by incorporating publicly available data sets to remove tiling array probe effects.
To make sure a uniform data distribution, the ComBat function from the sva package in R is applied to these two data sets to remove the batch effect.
A filtering step was applied to the initial 31099 probe sets to remove probes with detection calls labeled as "absent" across all five time points and corresponding to 5616 probe sets (Fig. 1).
We filtered both sets to remove the trials with duplicate sequences, i.e. so far we collected all trials with the complete stop (or current) status irrespective of the sequence.
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CEO of Professional Science Editing for Scientists @ prosciediting.com