[BioC] non-CpG methylated regions and strand information in MEDIPS output

Ioana [guest] guest at bioconductor.org
Thu Jul 31 22:55:39 CEST 2014


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  

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