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Each module contains genes with similar cell cycle expression profiles, and the overall expression profile of each module can be represented by the first eigenvector of the module.
A calculated inner product value of 0.91 indicated that the fluctuations described by the first eigenvector persist throughout the simulation, in contrast to motion described by other eigenvectors.
First two columns: Nb: number of animals in the considered group; %V1: % of variance explained by the first eigenvector of the VCV matrix between Fourier coefficients.
Global coherence is the fraction of variance at a given frequency across all EEG channels that is explained by the first eigenvector of the cross-spectral matrix.
A more detailed analysis of the S statistics was consistent with this interpretation: the largest contributions to S3 were made by the first eigenvector and occurred in comparisons involving the Su2 sample.
Spectral decomposition of the K matrix revealed that < 5% of the variation was captured by the first eigenvector.
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Contributions to the motions were specified by the first eigenvectors in sim-K1 and sim-K2 (31% and 32%, respectively) (Fig. 6A).
Each point represents one sample EXAFS spectrum in a coordinate space defined by the product of the first eigenvector (principal component, v1) and its sample-specific first eigenvalues (w1,i ) on the x-axis, plotted against the product of the second eigenvector (v2) and its sample-specific second eigenvalues (w2,i ) on the y-axis.
Thus, by projecting the initial data on the first eigenvector, we obtain the first extracted wavefield (wave 1) (Figure 10) and on the second eigenvector, the second extracted wavefield (wave 2) (Figure 11).
Despite including a part of intra-population variance, this direction is highly influenced by inter-population differences (correlation with the first eigenvector based on mean per populations only: UM1 |R| = 0.941, LM1 |R| = 0.995, P>0.999) and can be reliably estimated based on more than 200 specimens.
The genes are ordered from left to right by their coefficients in the first principal component (i.e., the first eigenvector), whereas the samples are ordered from top to bottom by their first principal component scores.
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by the maximum eigenvector
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