This is an old revision of the document!


ASCA-genes [2] is an adaptation of the ASCA method (ANOVA Simultaneous Component Analysis) [3] developed by Smilde and co-workers, to the analysis of multifactorial experiments in transcriptomics. Basically, ASCA uses ANOVA to decompose data variation associated to experimental factors, and PCA to discover principal patterns of variation associated to the experimental factors. ASCA-genes combines this multivariate descriptive analysis on time course expression data with a gene selection procedure. ASCA-genes has been implemented for designed experiments comprising either one, two or three experimental factors, one of them typically the time. The program returns trajectory charts representing major transcriptional changes and lists of selected genes that significantly follow these major changes. An additional list collects genes with expression profile changes different from the major trends.


  • Data: txt file with expression data, genes in rows, arrays in columns. The file must contain an additional row with arrays names and a column with gene names.


  • Covariates: txt file with experimental design information, containing as many columns as arrays and as many rows as experimental factor. Each cell contains the value of the array in the experimental factor. E.g:


  • Join: logical to indicate whether serial transcriptional changes should include time-zero non-null values (TRUE, default) or not (FALSE).
  • Interaction: logical to indicate whether interactions between factors should be analyzed.
  • Variability: average“ to explain more than the average variation of the principal components. A specific variation can be also indicated as 0.75 or 0.80…
  • alpha: significant level for gene selection.
  • R: number of bootstrap rounds for gene selection.

ascagenes.1267369724.txt.gz · Last modified: 2010/02/28 16:08 by aconesa
CC Attribution-Noncommercial-Share Alike 4.0 International Valid CSS Driven by DokuWiki do yourself a favour and use a real browser - get firefox!! Recent changes RSS feed Valid XHTML 1.0