Principal component analysis of pulmonary gene expression.

<p>An evolving gene expression profile was indicated after <i>B. pertussis</i> infection of naive mice (Mean of n = 3), illustrated as principal-component analysis (PCA). PCA is a mathematical algorithm <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0104548#pone.0104548-Raychaudhuri1" target="_blank">[117]</a>, which describes data based on (dis)similarity. Therefore, a greater distance between points in the plot corresponds to a greater dissimilarity. In this figure, the similarity of the 10 time points are compared based on the expression profiles of the 558 differentially expressed genes. Results indicate that 81% and 9% of the variance between time points could be addressed by principal component 1 (PC1) and PC2, respectively. The next principle components contribute for the residual variances. The plot revealed a notable change in gene expression at 2 days p.i. compared to 4 hours p.i., and largest differences at 14 days p.i. The gene expression at 28 days p.i. was still far from the naive state.