Hello everyone, I have a methylome dataset and a RNA-seq dataset and I want intersect each other in order to define the methylation status of differentially expressed genes of my interest.
To define the promoter region of all genes in the genome I used this code:
allproms <- promoters(TxDb.Hsapiens.UCSC.hg38.knownGene, downstream = 0, upstream = 2584)
but I’m not sure about the range to give to extract the informations,
My objective is to find out which promoters have methylated bases within their range. I am attempting to do this with the following lines of code:
library(plyranges)
metproms <- join_overlap_inner(allproms, metdat)
Where allproms is the object containing the coordinates and ranges of the promoters, and metdat the object with the ranges for the methylated bases.
Is there a better way to do that?
Thank you
1 answer
Based on my shallow experience, you may try:
- FEM, which statistically integrates: RNA-seq, Methylation, and PPI network.
- MOFA: Multi-Omics Factor Analysis. I used it for multi-omic clustering only.
I will encounter this problem like you soon in next month, so I am also looking for better tools or pure algorithms.
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