Dear Andrew,
I would like to congratulate you for the tool and the paper. I am really pretty intriguied by your paper and I am particularly interested in application of your tool in our Ovarian Cancer (OC) data set. I have downloaded the tool and while reading through the manual I realized that this tool works effectively for 450k beadchip array DNA methylation. I have few queries if you can address:
- I have DNA methyation data from normal and tumor of OC from 450k ( 8 normal and 7 tumor) and 850k (7 normal and 7 tumor). I also have RNA-Seq data of normal and tumor samples. When I say normal it means tissue of origin like fimbria and ovarian surface epithelium which act as normal. Tumor represents high grade serous epithelial ovarian carcinoma and advance Ascites. Now about the integration of 450k and 850k, will this tool work? I believe it should be able to if I only focus on the spots common between the 450k and 850k which means only 450k spots from both the runs. Please correct me if I am wrong.
- Coming to the second question , about the PPI network. I read the West et al., 2013 where it is mentioned that the PPI network is created with genes annotated with 27k infinium array for probes that pass QC just having 8k nodes and over 100,000 edges. Is this the same PPI network that was used in the Jiao, Yinming et al 2014 paper? Or the PPI now in this link http://sourceforge.net/projects/funepimod/files is based on 450k? I have been a bit confused with this. If you can elucidate. Since I am interested integrating DNA methylation data and RNA-Seq data of our Normal/Tumor to capture the epireg module that controles the expression, I thought of applying your tool. So if you could let me know about the PPI network that you created if that can be applied over 450k data integration with RNA-Seq in OC or not. I would like to know.
Sorry if it is too long but I could not find any better place to post the question, if you have any other links or issue tracker or a github where you prefer to put these questions. Please let me know. Waiting for your reply. Thanks a lot.