Agilent vs. Codelink vs. Applied?
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Ramon Diaz ★ 1.1k
@ramon-diaz-159
Last seen 9.6 years ago
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. -- Ram?n D?az-Uriarte Bioinformatics Unit Centro Nacional de Investigaciones Oncol?gicas (CNIO) (Spanish National Cancer Center) Melchor Fern?ndez Almagro, 3 28029 Madrid (Spain) Fax: +-34-91-224-6972 Phone: +-34-91-224-6900 http://ligarto.org/rdiaz PGP KeyID: 0xE89B3462 (http://ligarto.org/rdiaz/0xE89B3462.asc) **NOTA DE CONFIDENCIALIDAD** Este correo electr?nico, y en ...{{dropped}}
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@adaikalavan-ramasamy-675
Last seen 9.6 years ago
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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Dear Adai, Thanks a lot for your answer. You actually provide a lot of interesting suggestions, and I'll ask about some of these possible options. Yes, I looked at the nature Methods and the PNAS paper, but some of the platforms I was interested in were not included. The people I've talked to, they all seemed happy with the platform they were using, and that is why I was looking for possible comparisons. Best, R. On Tuesday 17 May 2005 21:02, Adaikalavan Ramasamy wrote: > 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. -- Ram?n D?az-Uriarte Bioinformatics Unit Centro Nacional de Investigaciones Oncol?gicas (CNIO) (Spanish National Cancer Center) Melchor Fern?ndez Almagro, 3 28029 Madrid (Spain) Fax: +-34-91-224-6972 Phone: +-34-91-224-6900 http://ligarto.org/rdiaz PGP KeyID: 0xE89B3462 (http://ligarto.org/rdiaz/0xE89B3462.asc) **NOTA DE CONFIDENCIALIDAD** Este correo electr?nico, y en ...{{dropped}}
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