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A summary of efficacy data at weeks 12 and 24 is presented in Table 2. Summary of efficacy outcomes at weeks 12 and 24 according to observed cases dataset analysis on the intent-to-treat population.
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A detailed microarray dataset analysis, based on clustering of similarly expressed genes (GEDI software), can detect underlying global-scale responses, which cannot be detected by means of individual gene expression techniques using raw or corrected p values (FDR).
Dataset analysis was performed on the Yale High Performance Computing Cluster.
Based on the dataset analysis, the study provides a global outlook of the targets' trajectory of all countries whose targets change.
Thus, export of DECT datasets and analysis on a separate machine was necessary.
The harmonized dataset allows for analysis on the individual level, and stratified analyses allow for studying cross-nation differences.
The dataset for the analysis on all-cause mortality was similarly constructed as for the analysis on MI, as is described above.
In order to validate the results obtained by the differential expressions analysis in our dataset, we perform differential analysis on two independent datasets.
When analyzing these bootstrap datasets, we perform complete CIM analysis on each one including determining appropriate background markers.
To validate that the common metastatic signature could be applied to other metastatic datasets, we performed Gene Set Expression Comparison analysis on six independent gene expression datasets identified through Oncomine that were not used in the meta-analysis.
To demonstrate the added values in combining multiple datasets, we also carried out connectivity mapping analysis on each dataset individually.
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CEO of Professional Science Editing for Scientists @ prosciediting.com