Hi Marcin.

Though I can't recommend you any company or research group for microarray data, I'd like to suggest RNA-seq instead of microarray. RNA-seq will give you more information with less monetary investment (in general). Also, RNA-seq can overcome some microarrays inherent problems, for example, cross hybridization between closely related sequences (as you won't hybridize, you'll sequence and count reads), detection of low abundance transcript, detection of new transcripts or splice events, etc. Also, you have a an advantage here as you are using mice: the genome is sequenced, which means your transcript assembly and data processing will be much easier (and right now, it's much easier to publish an RNA-seq paper than a MA one!). Seriously, it's not a coincidence that most of the people that have been using microarrays for long are now migrating to RNAseq based experiments.

Sorry for not answering to your question, still, I thought I would share that comment just in case you want to give it a try. I'm directing you to a 2008 Nature's letter about the subject (http://www.ncbi.nlm.nih.gov/pubmed/18587314). The letter comments on the two research articles that were published on that issue and that started the RNAseq "revolution". Again, sorry for not being more helpful.

In the Midwest, most of the centers have very similar and competitive rates for off campus projects. We have had success with the Universities of Iowa and Illinois, and I was happy with their customer service and final data analyses. If you can find a collaborator within an institution, you can often get drastically reduced prices. I believe this is the case for Washington University (in STL, not state), and while I have not used their services, I have only heard good things about their core.

Hi Marcin.

Though I can't recommend you any company or research group for microarray data, I'd like to suggest RNA-seq instead of microarray. RNA-seq will give you more information with less monetary investment (in general). Also, RNA-seq can overcome some microarrays inherent problems, for example, cross hybridization between closely related sequences (as you won't hybridize, you'll sequence and count reads), detection of low abundance transcript, detection of new transcripts or splice events, etc. Also, you have a an advantage here as you are using mice: the genome is sequenced, which means your transcript assembly and data processing will be much easier (and right now, it's much easier to publish an RNA-seq paper than a MA one!). Seriously, it's not a coincidence that most of the people that have been using microarrays for long are now migrating to RNAseq based experiments.

Sorry for not answering to your question, still, I thought I would share that comment just in case you want to give it a try. I'm directing you to a 2008 Nature's letter about the subject (http://www.ncbi.nlm.nih.gov/pubmed/18587314). The letter comments on the two research articles that were published on that issue and that started the RNAseq "revolution". Again, sorry for not being more helpful.

I will go by Gustavo.

I would prefer RNA-Seq over microarray analysis.

You can explore following:

www.genotypic.co.in

www.sandorproteomics.co.in

Both of them provide reliable service for both microarray and RNA-seq.

Thanks for all your tips!