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examples.development [2010/03/25 13:28]
mjnueda
examples.development [2010/05/05 10:39] (current)
mjnueda
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 ====== Development Example====== ====== Development Example======
  
- +Data:{{:subset_development_4t_data.zip|}}
-Data:{{:subset_hypoxia_4t_data.zip|}}+
 \\ \\
 Covariates:​{{:​development_covariates.txt|}} Covariates:​{{:​development_covariates.txt|}}
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 Variability associated to each factor: Variability associated to each factor:
   * Time 25.86 %   * Time 25.86 %
-  * Treatment+TimexTreatment 37.56 %+  * Treatment+TimexTreatment 37.52 %
   * Residuals 36.62 %   * Residuals 36.62 %
  
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 ====== ASCA-Functional ====== ====== ASCA-Functional ======
 +\\
 +By applying ASCA-Functional to the first component of the submodel Treatment+TimexTreatment and considering a significant level of 0.05 in the GSA analysis we detected as significant 13 functional categories.
 +The categories with an adjusted p-value less than 0.05 appear in the first two tables of the ASCA-Functional results.
 +\\
 +{{:​hypoxia_ascafunt.png?​600|}}
 +
 ====== maSigPro ====== ====== 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=0.8 and alpha=0.05 we obtained as significant:​ 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=0.8 and alpha=0.05 we obtained as significant:​
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   * 1100 categories with differences between the trajectories of the groups B and A.   * 1100 categories with differences between the trajectories of the groups B and A.
   * 1469 categories with differences between the trajectories of the groups C and A.   * 1469 categories with differences between the trajectories of the groups C and A.
- 
-maSigVisualization module for PCA-maSigFun offers two outputs: ​ 
-  - Output 1: Trajectory plots of clusters of categories, as in maSigFun. 
-  - Output 2:​{{:​categories_and_genes.pdf|A pdf file}} with the trajectory plots of each category next to a barplot with the correlation of each gene to the displayed trend. 
-The second output helps to understand the expression profile of the class and the participation of the class members in this profile. ​ 
  
examples.development.1269520083.txt.gz · Last modified: 2010/03/25 13:28 by mjnueda
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