Table of Contents
Arabidopsis Example
This is a study on the response of Arabidopsis leaves to treatment with Indol Acetic Acid at two different levels (HighIAA, and LowIAA). The dataset has two series and 2 time-points. (1 and 3 hours), plus the 0 time-point.
Data: arabidopsis_data.txt
Covariates:arabidopsis_cov.txt
ASCA-genes
Variability associated to each factor:
- Time 19.92 %
- Treatment+TimexTreatment 19.76 %
- Residuals 60.32 %
Variability explained for each submodel :
- With 1 component, Submodel Time explains 64.27% of variation of factor Time.
- With 1 component, Submodel Treatment+TimexTreatment explains 67.76% of variation of factor Treatment+TimexTreatment.
Trajectory plot of time submodel:
Trajectory plot of Treatment+TimexTreatment submodel:
ASCA-Functional
By applying ASCA-Functional to the first component of the second submodel 78 functional categories are selected by choosing a significant level of 0.05 in the GSA anlaysis and GO Biological Procceses annotations.
maSigPro
By applying maSigPro with degree=2, R-squared=0.7 and alpha=0.05 we obtained as significant:
- 590 genes with changes in Low-IAA trajectory.
- 549 genes with differences between High-IAA and Low-IAA trajectories.
As the most interesting genes are those with differences between both groups we represent in 9 groups the trajectories of the second gene-selection (549 genes).
In the following plot red colour represent the trend of Low-IAA group and green the High-IAA.
