[BioC] microarray analysis in R without replicates

[Thomas Hampton]

Rainer,

I think your experiment could yield many insights. Arrays are mostly  
about
hypothesis generation, not hypothesis testing anyway.

Clustering your samples should tell you which conditions may be
most similar. That should be interesting.

For any pair of comparisons, you are certainly entitled to observe fold
change differences of various genes, and you can take the most
highly regulated genes and see whether they belong to paths.

Just do some inexpensive low throughput experiments to validate anything
that your array analysis uncovers.

My two cents.

Tom


n Sep 22, 2009, at 3:16 PM, Rainer Tischler wrote:

> Komplettansicht
> Dear all,
>
> I
> have received a microarray data set in standard Affymetrix CEL-format
> consisting of only six samples  without any replicates (same organism
> and cell type, but different individuals and different biological
> conditions for each individual; the same Affymetrix GeneChip platform
> was used for all samples). Moreover, the data was apparently collected
> without any a-priori biological hypothesis.
>
> I know that it is
> impossible to apply standard clustering, feature selection or
> classification techniques in this case. However, I am wondering  
> whether
> anybody is aware of a method in R to extract meaningful biological
> information in this case (i.e. from single-sample microarray data or
> from multiple samples with different biological conditions and no
> replicates) - or is there nothing I can do given the above  
> limitations?
>
> Many thanks,
> Rainer
>
>
>
>
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