Kun:LabNotes/MONOD/2015-3-11
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Data analysis (continue)
- I wanted to be more systematic in analyzing the combined data from RRBS, SeqCap and BSPP experiments.
- A key is to define a set of bins (or windows) across the genome for haplotype extraction.
- My previous approaches were somewhat ad hoc, mostly based on read coverage in each group of data sets. I did try a number of different ways to split bigger windows into smaller ones for RRBS and SeqCap data, but none was systematic.
- The thought here is that we want to define a bin where there is some internal methylation haplotype structure. In other words, every CpG site should be linked to other sites in the same bin. So if we use the conception of methylation LD, the pair-wise LD for all sites in a bin should be above a certain threshold. Formally, we can partition all CpG sites in the entire genome into methylation LD blocks. Each block would be a bin for MONOD. I wrote a script hapInfo2mld_blocks.pl for this purpose.
- The next question is what data shall we use to define the bins. To be completely unbiased, we want to use WGBS data in the ideal situation.