[BioC] Agilent vs. Codelink vs. Applied?

Adaikalavan Ramasamy ramasamy at cancer.org.uk
Tue May 17 21:02:39 CEST 2005


Sorry, I have no experience with any of these arrays.

If you can spend a bit of money, then it might be worth investigating
their reproducibility (and perhaps the investigation might end up as an
article too).

I think you might be able to send your samples to these different
companies and ask them to do the hybridisation for you explaining that
you are interested in long term commitment if the hybridisation works
out. They may offer to do so at a special price.

Then unknown to them send some sample along with some repeat aliquots
(e.g. 5 biological samples x 3 aliquots = 15 "samples"). This way you
can assess the biological and technical variability when it is done
under the best procedures.

If you have more money, then give the same samples to someone who is
relatively new with microarray (e.g. PhD student?). Then calculate the
variability and compare with above. This would tell you how sensitive
each platform is to bad handling.

A modification of this is to spike in some genes of known concentration
or supplying the same sample to many different labs.

The following news articles covers 3 recent studies that compared the
effect of different platforms and labs. Try scanning them to see if the
platforms you mentioned are covered by these studies
http://focus.hms.harvard.edu/2005/May6_2005/comp_bio.shtml

If you do not have the money, then do a literature search and talk to
many people who have done the array.

Regards, Adai



On Tue, 2005-05-17 at 18:54 +0200, Ramon Diaz-Uriarte wrote:
> Dear All,
> 
> We are trying to decide on whether to use Agilent two-color arrays, Codelink 
> arrays or Applied Biosystems arrays (the last two are one-color) for a new 
> study. An advantage of the one-color platforms is that design-related issues 
> (loop, reference, all pairwise, etc) are no longer an issue. This is very 
> relevant in our case because we have 5 groups of very unequal sample sizes 
> and we´ll need to correct for the effect of several covariates, so finding an 
> optimal design seems difficult. 
> 
> I've seen several recent posts in the lists concerning Codelink arrays. I 
> wonder if anybody has any comparison among these platforms (specially if 
> forced to use a common reference design for the two-color arrays), or any 
> experience with the Applied Biosystems arrays.
> 
> Best,
> 
> R.
>



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