Hello, I am using the MEDIPS package for analysing differentially methylated regions in sets of stem cells (embryonic stem cells and trophoblasts). I am wondering whether there is any way in which I could retrieve strand information for the DMRs in the output in order to determine whether methylation is non-CpG (asymmetric - only appears on one strand) or CpG. There is no mention of this in the vignette of the package despite the fact that the data sets used also come from embryonic stem cells which show non-CpG methylation. I am asking regarding this issue because when I try to annotate the DMRs obtained, I am taking both strands into account for the genomic coordinates obtained which might not be accurate because not both strands are methylated (non-CpG methylation). I am using biomaRt and GenomicRanges for obtaining information about which promoters/gene regions overlap with the DMRs. Thank you very much for your help. The maintainer of the package information: packageDescription('MEDIPS')$Maintainer [1] "Lukas Chavez <lchavez at="" liai.org="">" -- output of sessionInfo(): R version 3.1.1 (2014-07-10) Platform: x86_64-pc-linux-gnu (64-bit) locale: [1] LC_CTYPE=en_GB.UTF-8 LC_NUMERIC=C [3] LC_TIME=en_GB.UTF-8 LC_COLLATE=en_GB.UTF-8 [5] LC_MONETARY=en_GB.UTF-8 LC_MESSAGES=en_GB.UTF-8 [7] LC_PAPER=en_GB.UTF-8 LC_NAME=C [9] LC_ADDRESS=C LC_TELEPHONE=C [11] LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C attached base packages: [1] parallel stats graphics grDevices utils datasets methods [8] base other attached packages: [1] BSgenome.Mmusculus.UCSC.mm9_1.3.1000 BiocInstaller_1.14.2 [3] ggplot2_1.0.0 biomaRt_2.20.0 [5] MEDIPS_1.14.0 rtracklayer_1.24.2 [7] Rsamtools_1.16.1 DNAcopy_1.38.1 [9] edgeR_3.6.5 limma_3.20.8 [11] gtools_3.4.1 BSgenome_1.32.0 [13] Biostrings_2.32.1 XVector_0.4.0 [15] GenomicRanges_1.16.3 GenomeInfoDb_1.0.2 [17] IRanges_1.22.9 BiocGenerics_0.10.0 -- Sent via the guest posting facility at bioconductor.org.

Dear Iona, there is no function available for a strand specific analysis of DNA IP-seq data. In principal, you can calculate 'strand specific' coverage and 'strand specific' differential coverage by separating your bam file into two files, one containing only hits that align to the plus and the other file containing only hits that align to the minus strand. Subsequently you can apply MEDIPS to each of the strand separated bam files individually. However, I am wondering, if your DNA IP-seq data is really strand specific so that it will allow you to infer strand specific methylation? Moreover, I do not see how you intend to discriminate between CpG and non-CpG methylation based on 'strand specific' coverage? Best regards, Lukas On Thu, Jul 31, 2014 at 1:55 PM, Ioana [guest] <guest@bioconductor.org> wrote: > Hello, > > I am using the MEDIPS package for analysing differentially methylated > regions in sets of stem cells (embryonic stem cells and trophoblasts). I am > wondering whether there is any way in which I could retrieve strand > information for the DMRs in the output in order to determine whether > methylation is non-CpG (asymmetric - only appears on one strand) or CpG. > > There is no mention of this in the vignette of the package despite the > fact that the data sets used also come from embryonic stem cells which show > non-CpG methylation. > > I am asking regarding this issue because when I try to annotate the DMRs > obtained, I am taking both strands into account for the genomic coordinates > obtained which might not be accurate because not both strands are > methylated (non-CpG methylation). I am using biomaRt and GenomicRanges for > obtaining information about which promoters/gene regions overlap with the > DMRs. > > Thank you very much for your help. > > The maintainer of the package information: > packageDescription('MEDIPS')$Maintainer > [1] "Lukas Chavez <lchavez@liai.org>" > > > > > -- output of sessionInfo(): > > R version 3.1.1 (2014-07-10) > Platform: x86_64-pc-linux-gnu (64-bit) > > locale: > [1] LC_CTYPE=en_GB.UTF-8 LC_NUMERIC=C > [3] LC_TIME=en_GB.UTF-8 LC_COLLATE=en_GB.UTF-8 > [5] LC_MONETARY=en_GB.UTF-8 LC_MESSAGES=en_GB.UTF-8 > [7] LC_PAPER=en_GB.UTF-8 LC_NAME=C > [9] LC_ADDRESS=C LC_TELEPHONE=C > [11] LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C > > attached base packages: > [1] parallel stats graphics grDevices utils datasets methods > [8] base > > other attached packages: > [1] BSgenome.Mmusculus.UCSC.mm9_1.3.1000 BiocInstaller_1.14.2 > [3] ggplot2_1.0.0 biomaRt_2.20.0 > [5] MEDIPS_1.14.0 rtracklayer_1.24.2 > [7] Rsamtools_1.16.1 DNAcopy_1.38.1 > [9] edgeR_3.6.5 limma_3.20.8 > [11] gtools_3.4.1 BSgenome_1.32.0 > [13] Biostrings_2.32.1 XVector_0.4.0 > [15] GenomicRanges_1.16.3 GenomeInfoDb_1.0.2 > [17] IRanges_1.22.9 BiocGenerics_0.10.0 > > -- > Sent via the guest posting facility at bioconductor.org. > > _______________________________________________ > Bioconductor mailing list > Bioconductor@r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor > [[alternative HTML version deleted]]