Integrating Genomics Data From Different Platform

Question

[datanerd]

Hi all,

I have read a lot about the need for data integration and its added value in data interpretation. We have been trying to do this with some data we have already generated. I recently attended a conference and it had great talks about the methods for integrating genomic data. But most of it are still being developed. I tried to look for what methods are being used but couldn't find anything that could help. I would like to know if anyone is familiar with integrating miRNA, methylation and mRNA (and/or proteomics) data using a statistical (bayesian or?) approach. Any paper, review, information, package or tool will help! Any suggestion will be highly appreciated! Thanks in advance!

[Ketil]

Maybe this question would be easier to answer if it were more concrete? What data have you generated, and how are you trying to interpret it, and how/why would those other data be used to aid interpretation?

[datanerd]

Sorry for being unclear. I have mRNA, methylation and miRNA data from the same samples. I would want to know by the biological relationship among the different data, what significant mRNA in my data are regulated by methylation or miRNA or both using some statistical approach. even if I just get those list, that would help me.

Answer 1

[Irsan]

Though I agree with Ketil, I think you might find the Bioconductor SIM-package useful. I have not used it myself yet (will do so in the near future) but it is developed to integrate various kinds of human genomics data.

[datanerd]

Thanks Irsan, I will look into that package. I found this paper using iBAG model for integrating genomic data http://www.ncbi.nlm.nih.gov/pubmed/23142963 Would appreciate your incite on this.