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Data pre-processing and normalization: Data quality assessment was followed by data pre-processing and normalization with the Robust Multi-Array Average (RMA) algorithm [ 55], implemented in the RMA function in the Bioconductor Affy package [ 56].
(3) Data set feature normalization Data standardization (normalization) processing is a basic work of data mining.
Comparison of homogenization of hybridization signals from the normalized probe to the non-normalized probe indicated the efficiency of normalization (data not shown).
All GC/MS data were expressed relative to U-13C-sorbitol and extract replicates averaged after TIC normalization (Data S1).
We describe seven steps of data processing: collection of data from heterogeneous sources, data normalization, data brokering, data storage, data analysis, data visualization and decision support systems.
The paper includes review and discussion of electrode site location, methods of normalization, data reliability, and factors that can affect sEMG signals from this region, including noise, physiologic artifact, stress, visual deficiencies, and pain.
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The box-plots of before- and after-normalization data clearly indicated that the normalization removed the across-array bias and rendered the data distribution more consistent among the 6 data files (Figure 2).
We performed QC on both the pre- and post-normalization data.
Clusters on pre-normalization data are not grouped by patient, extraction or dilution (100 or 200 ng) (see Additional file 7).
Clusters on both pre- and post-normalization data are not grouped by either patient or dilution (100 or 200 ng) (see Additional files 9 and 10).
This median normalization was performed in log-transformed absolute expression values, thus making post-normalization data somewhat similar to the log ratios captured by two-channel arrays.
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