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We chose the best MDR model for each SNP and assigned that SNP the corresponding MDR model p-value.
IC50 (50% inhibitory concentration) value of DOX AcFu was lower than that of free DOX in the MDR model cells.
Cross-validation consistency is a measure of the number of times an MDR model is identified in each possible group of nine-tenths of the subjects.
One advantage of this type of MDR model compared to logistic regression is that there is no need to specify an arbitrary threshold value for classifying risk status.
Given the sample size of the available datasets and the number of factors in the model, the somewhat decreased performance of the MDR model is not unexpected.
In the MDR model, there was a clear tendency for individuals with more risk alleles/risk factors present and fewer protective alleles to be classified by the model as "high-risk" and vice versa, as expected (data not shown).
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This left us with 21 individual SNPs or SNP groups as candidate attributes for our MDR models.
The topology of the graph, consisting of SNPs and their pairwise interactions, was used to guide MDR modeling.
The optimal one-locus, two-locus, and three-locus MDR models with the highest testing accuracy are identified.
By pooling moderate and inter-related genetic contributors together, the A-MDR model becomes robust and predictive of complex traits.
In this work, we have proposed an Aggregated Multifactor Dimensionality Reduction (A-MDR) model to elucidate complex and non-linear genetic associations contributing to disease risk and variability in response to treatment.
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