Each color corresponds to a different batch. A = per batch normalization with no QCs, B = per batch normalization with QC correction, C = merged normalization with no QCs, D = merged normalization with QC correction.</p
Color data as interpreted in a color opponency framework. Raw color data are provided along with nor...
<p>(A) PCA of individual experimental samples in NC47. (B) PCA of 69 differentially accumulated prot...
<p>The code corresponds to the cultivar (M: Melrose, S: Smoothee, A: Ariane), to the management syst...
<p>The first order samples are shown in green, the second order samples are shown in red, and the th...
Extensive overload of data obtained from batch processes see the need for reduced dimensional analys...
(A) PCA of the expression matrix fails to reveal clustering by population, whereas (B) PCA of the ge...
<p>Cancer subjects are labelled in red, controls in blue and QCs in green. The vector from diamond t...
<p>Principal component analysis (PCA) plot for combined dataset before (left panel) and after (right...
The PCA1 and PCA2 columns are the errors for a PCA using two different column scalings.</p
Non-normalized (top left), min-max normalization (top right). quantile normalization (bottom left), ...
<p>Blue dots are CRC samples with CRP <30 and purple dots are samples with CRP >30. The PCA was perf...
Principle component analysis (PCA) of all samples. Low-iron samples are shown in blue, high-iron in ...
<p>The values of Macro-Precision, Macro-Recall, Macro-F1 and Micro-F1 under different number of feat...
<p>PCA item loadings for 6-factor solution of screening items, from the full sample and by sub-group...
Principal components analysis (PCA) is a multivariate ordination technique used to display patterns ...
Color data as interpreted in a color opponency framework. Raw color data are provided along with nor...
<p>(A) PCA of individual experimental samples in NC47. (B) PCA of 69 differentially accumulated prot...
<p>The code corresponds to the cultivar (M: Melrose, S: Smoothee, A: Ariane), to the management syst...
<p>The first order samples are shown in green, the second order samples are shown in red, and the th...
Extensive overload of data obtained from batch processes see the need for reduced dimensional analys...
(A) PCA of the expression matrix fails to reveal clustering by population, whereas (B) PCA of the ge...
<p>Cancer subjects are labelled in red, controls in blue and QCs in green. The vector from diamond t...
<p>Principal component analysis (PCA) plot for combined dataset before (left panel) and after (right...
The PCA1 and PCA2 columns are the errors for a PCA using two different column scalings.</p
Non-normalized (top left), min-max normalization (top right). quantile normalization (bottom left), ...
<p>Blue dots are CRC samples with CRP <30 and purple dots are samples with CRP >30. The PCA was perf...
Principle component analysis (PCA) of all samples. Low-iron samples are shown in blue, high-iron in ...
<p>The values of Macro-Precision, Macro-Recall, Macro-F1 and Micro-F1 under different number of feat...
<p>PCA item loadings for 6-factor solution of screening items, from the full sample and by sub-group...
Principal components analysis (PCA) is a multivariate ordination technique used to display patterns ...
Color data as interpreted in a color opponency framework. Raw color data are provided along with nor...
<p>(A) PCA of individual experimental samples in NC47. (B) PCA of 69 differentially accumulated prot...
<p>The code corresponds to the cultivar (M: Melrose, S: Smoothee, A: Ariane), to the management syst...