Dear R users, I try to use Limma package to analyze methylation databases generated from Agilent CpG Islanfds, but i dont know if this is relevant because i have 4 groups ( one replicate for each group) ?? Can you please suggest me a method to analyze my data ? Any help will be appreciated Regards [[alternative HTML version deleted]]

Dear Mohamed, There are two ways to do methylation profiling, one with DMH and other with MeDIP technique. Therefore it is better to provide information of which method you use? In case, DMH, you can go ahead with Limma, as DMH data is linear to methylation level, otherwise use MEDME, which takes care of the non - linear nature of  methyaltion levels generated by MeDIP technique. Regards, Prashantha Lecturer, Dept. of Biotechnology, Manipal Life Sciences Center, Manipal University, Manipal, India PIN: 576104 Email:prashantha.hebbar@manipal.edu Phone: +91-9886359007 --- On Wed, 6/16/10, Mohamed Lajnef <mohamed.lajnef@inserm.fr> wrote: From: Mohamed Lajnef <mohamed.lajnef@inserm.fr> Subject: [BioC] Agilent CpG islands-Limma To: bioconductor@stat.math.ethz.ch Date: Wednesday, June 16, 2010, 1:43 PM Dear R users, I  try to use Limma package  to analyze methylation databases generated from Agilent CpG Islanfds, but i dont know if this is relevant because i have 4 groups ( one replicate for each group) ?? Can you please  suggest me a method to analyze my data ? Any help will be appreciated Regards     [[alternative HTML version deleted]] _______________________________________________ Bioconductor mailing list Bioconductor@stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/bioconductor Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor [[alternative HTML version deleted]]

Hi Mohamed, Please go through following paper on MEDME, http://www.ncbi.nlm.nih.gov/pubmed/18765822 Wherein author has explained the way they have done data analysis. After reading if you need any help, please let me know. Regards, Prashantha Hebbar Kiradi, Lecturer, Dept. of Biotechnology, Manipal Life Sciences Center, Manipal University, Manipal, India PIN: 576104 Email:prashantha.hebbar@manipal.edu Phone: +91-9886359007 --- On Thu, 6/17/10, Mohamed Lajnef <mohamed.lajnef@inserm.fr> wrote: From: Mohamed Lajnef <mohamed.lajnef@inserm.fr> Subject: Re: [BioC] Agilent CpG islands-Limma To: "Prashantha Hebbar" <prashantha.hebbar@yahoo.com> Date: Thursday, June 17, 2010, 8:04 AM Prashantha, Thank you for your answer, MeDIP protocol is used  for our project! But i have files in text format with ( Mean 635, Mean 532, Median 635,Median 532, .......) obtained from Agilent CpG islands. I thought that Limma is adapted for this kind of file! I  looked at the MEDME package, but i dont have the same kind of file ( GFF, SGR) Can I change my text file in GFF file to run MEDME package? Thank you again for your help Prashantha Regards mohamed Le 17/06/10 08:43, Prashantha Hebbar a écrit : Dear Mohamed, There are two ways to do methylation profiling, one with DMH and other with MeDIP technique. Therefore it is better to provide information of which method you use? In case, DMH, you can go ahead with Limma, as DMH data is linear to methylation level, otherwise use MEDME, which takes care of the non - linear nature of  methyaltion levels generated by MeDIP technique. Regards, Prashantha Lecturer, Dept. of Biotechnology, Manipal Life Sciences Center, Manipal University, Manipal, India PIN: 576104 Email:prashantha.hebbar@manipal.edu Phone: +91-9886359007 --- On Wed, 6/16/10, Mohamed Lajnef <mohamed.lajnef@inserm.fr> wrote: From: Mohamed Lajnef <mohamed.lajnef@inserm.fr> Subject: [BioC] Agilent CpG islands-Limma To: bioconductor@stat.math.ethz.ch Date: Wednesday, June 16, 2010, 1:43 PM Dear R users, I  try to use Limma package  to analyze methylation databases generated from Agilent CpG Islanfds, but i dont know if this is relevant because i have 4 groups ( one replicate for each group) ?? Can you please  suggest me a method to analyze my data ? Any help will be appreciated Regards     [[alternative HTML version deleted]] _______________________________________________ Bioconductor mailing list Bioconductor@stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/bioconductor Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor [[alternative HTML version deleted]]