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Development Example

ASCA-genes

Variability associated to each factor:

  • Time 25.86 %
  • Treatment+TimexTreatment 37.56 %
  • Residuals 36.62 %

Variability explained for each submodel :

  • With 2 components, Submodel Time explains 93.66% of variation of factor Time. (Component 1: 49.66% and Component 2: 44%).
  • With 2 components, Submodel Treatment+TimexTreatment explains 71.86% of variation of factor Treatment+TimexTreatment.(Component 1: 44.18% and Component 2: 27.67%).



ASCA-Functional

maSigPro

General trends showed with ASCA-genes module suggest that a quadratic model can be adequate to study gene expression evolution. By applying maSigPro with degree=2 (the quadratic model), R-squared=0.7 and alpha=0.05 we obtained as significant:

  • 1307 genes with changes in the trajectory of A.
  • 1158 genes with differences between the trajectories of the groups B and A.
  • 1282 genes with differences between the trajectories of the groups C and A.

We represent in 9 groups the trajectories of the second gene-selection (1158 genes).


?500

maSigFun

By applying maSigFun with degree=2, R-squared=0.4, alpha=0.05 and annotations GO biological process of Human organism we selected as significant the following categories:

  • GO:0006842 tricarboxylic acid transport
  • GO:0010544 negative regulation of platelet activation
  • GO:0015746 citrate transport

The trajectory plots of these categories are the following: hypo_3go_masigfun.pdf

PCA-maSigFun

examples.development.1269512110.txt.gz · Last modified: 2010/03/25 11:15 by mjnueda
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