<p>The first (PC1) and the second (PC2) principal components are represented.</p
The x, y, and z axes are the first, second, and third components that together capture most of the v...
The figure shows the first two principal components after merging the acquired datasets. The samples...
<p>Panel (a) plots the proportion of variance explained by principal components 1–4. Panel (b) is a ...
Circles represent young (7-weeks-old) plants while older (13-weeks-old) plants are represented by tr...
<p>Principal Component Analysis (PCA) of microarray data. PCA two-dimensional scatter plot represent...
<p>PCA plot shows the first three principal components of microarray data in respect to their correl...
<p>Principal component analysis (PCA) plot showing the grouping of the almond accessions.</p
<p>Bi-plots of the first two principal components F1 and F2. a) PCA including bi-plots based on agro...
<p>Principal component analysis (PCA) indicating the two different growth conditions (co-culture ver...
<p>The PCA of genes differentially expressed between active and regressed phase. Upper panel shows P...
<p>The color codes for each time point are shown on the top right corner. The three axes PC1, PC2, a...
Principal component analysis (PCA) was performed using the prcomp function from the R base package. ...
PCA of the quantile normalized dataset consisting of 32 mouse uterine RNA samples. The colours repre...
<p>(A) PCA of 1,444 GBS-derived SNPs without missing data in any of the accessions. (B) PCA of six p...
<p>Plot represents 1<sup>st</sup> (X-axis) and 2<sup>nd</sup> (Y-axis) principal components. Varianc...
The x, y, and z axes are the first, second, and third components that together capture most of the v...
The figure shows the first two principal components after merging the acquired datasets. The samples...
<p>Panel (a) plots the proportion of variance explained by principal components 1–4. Panel (b) is a ...
Circles represent young (7-weeks-old) plants while older (13-weeks-old) plants are represented by tr...
<p>Principal Component Analysis (PCA) of microarray data. PCA two-dimensional scatter plot represent...
<p>PCA plot shows the first three principal components of microarray data in respect to their correl...
<p>Principal component analysis (PCA) plot showing the grouping of the almond accessions.</p
<p>Bi-plots of the first two principal components F1 and F2. a) PCA including bi-plots based on agro...
<p>Principal component analysis (PCA) indicating the two different growth conditions (co-culture ver...
<p>The PCA of genes differentially expressed between active and regressed phase. Upper panel shows P...
<p>The color codes for each time point are shown on the top right corner. The three axes PC1, PC2, a...
Principal component analysis (PCA) was performed using the prcomp function from the R base package. ...
PCA of the quantile normalized dataset consisting of 32 mouse uterine RNA samples. The colours repre...
<p>(A) PCA of 1,444 GBS-derived SNPs without missing data in any of the accessions. (B) PCA of six p...
<p>Plot represents 1<sup>st</sup> (X-axis) and 2<sup>nd</sup> (Y-axis) principal components. Varianc...
The x, y, and z axes are the first, second, and third components that together capture most of the v...
The figure shows the first two principal components after merging the acquired datasets. The samples...
<p>Panel (a) plots the proportion of variance explained by principal components 1–4. Panel (b) is a ...
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