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The studies were conducted independently of each other and there were variations in the approach to the analyses.
This study demonstrates the power of bioinformatics approach to the analyses of promoter occupancy profiles of highly homologous transcription factors.
The approach to the analyses of a larger sample here described might serve to validate the technique.
The general approach to the analyses is guided by our own experience in the analyses of such data 43 44 and by recent reviews of best methods for analyses of longitudinal data from clinical trials.
As an alternative approach to the analyses, we used g:Profiler (Bioinformatics, Algorithmics and Data Mining Group 2011), which interprets gene lists by identifying enriched protein protein interactions using the BioGRID database (BioGRID 2011).
We evaluated an alternative approach to the analyses described above, by pre-adjusting the phenotypes for contemporary groups, and then allocating animals to pools across breeds and contemporary groups.
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We took three approaches to the analyses by evaluating associations with OS at the individual SNP level, gene level, and pathway level.
An approach to the performance analyses of given SSC diversity receiver is presented.
Thus, this preliminary study provides validation for our approach to the statistical analyses of array data.
MG developed the approach to the statistical analyses of the data.
The previous designs each use a frequentist approach to the primary analyses.
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