Selected article for: "cc NC International license and correlation coefficient"

Author: Héctor Cervera; Silvia Ambrós; Guillermo P. Bernet; Guillermo Rodrigo; Santiago F. Elena
Title: Viral fitness predicts the magnitude and direction of perturbations in the infected host transcriptome
  • Document date: 2017_10_20
  • ID: 0qmsripp_9
    Snippet: Regarding individual genes, two major clusters can be distinguished, one corresponding to the over-expression of genes related to stress response and a second one corresponding to the underexpression of genes involved with metabolism and plant development. To further explore the similarity in the perturbation induced by each viral genotype into the plants' transcriptome, we computed all pairwise Pearson product-moment correlation coefficients (r).....
    Document: Regarding individual genes, two major clusters can be distinguished, one corresponding to the over-expression of genes related to stress response and a second one corresponding to the underexpression of genes involved with metabolism and plant development. To further explore the similarity in the perturbation induced by each viral genotype into the plants' transcriptome, we computed all pairwise Pearson product-moment correlation coefficients (r) between the mean expression values for all genes in the microarray. Then, these correlations were used as a measure of similarity to build a UPGMA dendrogram. The rationale for this analysis is as follows: the more correlated two expression profiles are, the more similar the effects induced in infected plants. When comparing expression profiles from a pair of infected plants, a significant correlation may indicate that genes that changed expression relative to the mock-inoculated plants, are exactly the same in both samples, showing a similar expression pattern. If this is the . CC-BY-NC-ND 4.0 International license author/funder. It is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10.1101/206789 doi: bioRxiv preprint case, the correlation coefficient is expected to be high. Conversely, if genes with differential expression do not match in the two samples being compared, then the correlation will be lower. Three clusters result from this analysis (Fig. 3B) show the most dissimilar gene expression profile. The heat-map is shown with viral genotypes ordered according to the UPGMA clustering. Obviously, it is symmetric, with the diagonal corresponding to the correlation between profiles from plants infected with the same viral genotype, thus being r » 1. Correlations decreased as the distance in the cladogram increases.

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