I am analyzing 4 MeDIP Seq samples. I wanted to know, how do I create ROI. As of now, I do not have any shortlisted regions, I want to look at entire human genome. How to get it done.
Thanks in advance for any help.
Vivek
Hi Vivek,
in qsea, makeTable offers two possibilities to look at regions of interest (ROIs):
The "ROIs" parameter takes a GRange object selects all windows that overlap with these Genomic Ranges. Windows overlapping with more than one ROI are represented several times.
The "annotation" parameter takes a list of GRange objects (e.g. CpG islands, promoters, TFBS) and annotates the resulting table with the information from the GRanges. For each element of the list one column will be added, containing information from the metadata columns (mcols) of the overlapping GRanges. This is described in step 3.6 "Annotating, Exploring and Exporting Results" of the tutorial.
Additionally, you can compute the number of overlapping DMRs per class of ROIs using the regionStats() function, such as outlined in the tutorial. These numbers can then be used for overrepresentation analysis.
You can create GRanges from tables, for example downloaded from the UCSC table browser for the genome build you are using. For details look at the vignettes of "makeGRangesFromDataFrame()" and "GRanges()" functions of the GenomicRanges package.
Best, Matthias
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version 2.3.6
Dear Matthias,
Thank you for explaining this in detail. I still stuck with one place, ROIs is used in the below step,
result=makeTable(qseaSet, glm=qseaGLM, groupMeans=getSampleGroups(qseaSet), keep=sig, annotation=ROIs, norm_method="beta")
I guess this has been taken directly from data(annotation, package="MEDIPSData"). Is there a way to create it for entire genome within QSEA..? Or maybe directly annotated every region identified through maketable command.
Thanks in advance,
Vivek
Dear Vivek,
retrieving annotation is not within the scope of qsea. You are right, for the tutorial I provide a example for the analyzed chromosomes. You can create these objects yourself, by downloading tables from the UCSC table browser, import them in R (e.g. by read.table()) and then create a GRange object from it, using "makeGRangesFromDataFrame()" or "GRanges()". Alternativly, you can have a look at the annotation packages in bioconductor, such as outlined in this presentation: https://www.bioconductor.org/help/course-materials/2014/ISMB2014/Annotation_slides.pdf