<p>Models are: K-nearest-neighbor (KNN); Regularized Linear model (Elastic-Net); single best-SNP (Single SNP) or in any one of them (All models). Shown are the number of genes that pass training and test R<sup>2</sup> threshold (test/training) using the different models in the Cross-Pop cross-validation scheme.</p
<p>Pairwise variation (V<sub>n/n+1</sub>) analysis between the normalization factors NF<sub>n</sub> ...
Gene-based tests of association are frequently applied to common SNPs (MAF>5%) as an alternative to ...
<p>A) Error rate produced by different classification algorithms as a function of the number of pred...
<p>Models are: K-nearest-neighbor (KNN); Regularized Linear model (EN); single best-SNP (SS) or in a...
The average test set accuracy rates and the average numbers of selected genes of ten runs of fivefol...
<p>Shown are the 8 genes for which the KNN algorithm that integrated genomic features resulted in th...
<p>(A) Shown is a comparison of the training R<sup>2</sup> values for genes in either the basic KNN ...
##<p>The types of training genes used in the training model. The number of validated genes = 3,432...
<p>Average number of SNPs reaching the specified <i>p</i>-value thresholds for at least one of the t...
The average F-scores and the average numbers of selected genes of ten runs of fivefold cross-validat...
<p>At each score threshold, genes with a score greater than the threshold were classified as HK gene...
<p>1) Define at least two distinct groups of genes expected to be similar. 2) Compute the intra- and...
(A) Comparison of predictive performance for each gene (R2) between each pair of populations. Predic...
(A) 95% confidence intervals of the DEG F-scores of each machine learning approach across all regula...
1<p>P-value <0.0001;</p>2<p>Root mean square errors (RMSE) for the models using the training (T) and...
<p>Pairwise variation (V<sub>n/n+1</sub>) analysis between the normalization factors NF<sub>n</sub> ...
Gene-based tests of association are frequently applied to common SNPs (MAF>5%) as an alternative to ...
<p>A) Error rate produced by different classification algorithms as a function of the number of pred...
<p>Models are: K-nearest-neighbor (KNN); Regularized Linear model (EN); single best-SNP (SS) or in a...
The average test set accuracy rates and the average numbers of selected genes of ten runs of fivefol...
<p>Shown are the 8 genes for which the KNN algorithm that integrated genomic features resulted in th...
<p>(A) Shown is a comparison of the training R<sup>2</sup> values for genes in either the basic KNN ...
##<p>The types of training genes used in the training model. The number of validated genes = 3,432...
<p>Average number of SNPs reaching the specified <i>p</i>-value thresholds for at least one of the t...
The average F-scores and the average numbers of selected genes of ten runs of fivefold cross-validat...
<p>At each score threshold, genes with a score greater than the threshold were classified as HK gene...
<p>1) Define at least two distinct groups of genes expected to be similar. 2) Compute the intra- and...
(A) Comparison of predictive performance for each gene (R2) between each pair of populations. Predic...
(A) 95% confidence intervals of the DEG F-scores of each machine learning approach across all regula...
1<p>P-value <0.0001;</p>2<p>Root mean square errors (RMSE) for the models using the training (T) and...
<p>Pairwise variation (V<sub>n/n+1</sub>) analysis between the normalization factors NF<sub>n</sub> ...
Gene-based tests of association are frequently applied to common SNPs (MAF>5%) as an alternative to ...
<p>A) Error rate produced by different classification algorithms as a function of the number of pred...
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