Table 2.
Principal component analysis of cell-level data. Eigenvectors, in columns, are the arrays of four coefficients or weights used to generate the principal components as linear combinations of the variables listed in the first column. The rank (1–4) of a principal component is determined by its variance (eigenvalues). Note the large value of eigenvalue 1 and the comparable values of coefficients in principal component 1.
| Eigenvectors |
||||
|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |
| Resting [Ca2+]cyto | 0.41 | 0.18 | –0.86 | –0.26 |
| Spontaneous Ca2+ events | 0.59 | –0.30 | 0.41 | –0.62 |
| Evoked Ca2+ waves | 0.16 | 0.94 | 0.30 | –0.10 |
| Evoked Ca2+ spikes | 0.67 | –0.07 | 0.09 | 0.73 |
| Eigenvalues | 1.71 | 0.98 | 0.87 | 0.38 |