[BioC] time-course experiments/order-restricted

Vincent Carey 525-2265 stvjc at channing.harvard.edu
Wed Oct 8 12:11:47 MEST 2003

> Dear all,
> I am now working on some time-course experiments and I
> have applied to them some classical statistic methods
> to identify genes that change their expression between
> time points. However I have read few papers (such as
> Peddada et al. Gene selection and clustering for
> time-course and dose–response microarray experiments
> using order-restricted inference; GUO, X et al
> Statistical significance analysis of longitudinal gene
> expression data; etc..) where they describe specific
> methods for the analysis of this type of data.
> Unfortunately my background (I am biologist) make
> difficult to transform the algorithms reported in
> these papers in something usable in R. In the same
> time, I could not find packages in bioconductor that
> face this kind of problems ( there is only GeneTS
> written by Korbinian Strimmer, that is useful in a
> cyclic time-course experiment).

I believe you are correct that nothing directly confronts
time-course experiments.  But many existing tools can be used
for such data.

1) Data structure.  the exprSet class can be used, regarding
time elapsed as a component of the phenotype data.  the
values of the time element induce an order across all

2) Example.  The Iyer517 data package is an example based
on a celebrated paper on response of human fibroblasts
to exposure to serum.

3) Methods.
   a) Clustering.  The repeated observations on each gene can be
regarded as multivariate outcomes to be grouped by one's
favorite clustering method.
   b) visualization.  MASS parallel coordinate plots are
useful; you can use ggobi with Iyer517 for a dynamic display.

I have to run now, we can add some material to the Iyer517 vignette
to get more precision on these recommendations and add additional

PS -- get the order-restricted folks to contribute their

> I was wondering if anybody has already developed a
> package or some functions usable in R specifically
> designed for time-course experiment that consider the
> particular structure of this data. Otherwise is there
> anybody interest in developing something from scratch?
> Thank you very much in advance for your help.
> Best wishes,
> edoardo
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