A few more details on this data preparation procedure are described below.
We use the data preparation procedure described in [ 22].
At the end of the data preparation procedure, SNPTracker reads the SNPChrPosOnRef dataset to retrieve coordinates for all input variants.
For the prediction of external data, such a separate data preparation procedure may be suitable in some situations, for example when the external data behaves very differently from the training data: by a separate processing the data preparation procedure can adjust itself to the peculiarities of the external data; see e.g. [ 16].
Standard data preparation and enhancement procedures including refraction statics correction, noise attenuation, deconvolution and common midpoint sorting (CMP) were carried out to improve data signal-to-noise ratio.
However, to avoid experimental deviations or the errors that inevitably occur during sample preparation procedures and data analysis, all of which make quantitation of gene transcripts unreliable, normalization of the qRT-PCR data is essential.
Preparation, procedures, instrumentation, data acquisition and results analysis, interpretation and reporting for experimental testing ranging from whole vehicle braking performance on a test track to component performance and material thermophysical properties in the laboratory, are explained and discussed.
We found that samples representing different leukemia subclasses and extracted using different RNA preparation methods are characterized by a high comparability of gene expression data thus demonstrating that sample preparation procedures do not impair the overall probe set signal intensity distribution.
The data mining procedures used for data preparation, modeling and simulation, which include statistics, methods of artificial intelligence and hybrid models in form of cascade committee machines, are described.
