Raw reads (RRBS, Illumina HiSeq, 150PE) were trimmed using Trim Galore v0.4.1. The filtered reads were mapped to the mouse genome (GRCm38/mm10) using Bismark v0.15.0.
cov-to-metcov.R was used to process files obtained in the previous step to get methylation level from counts of reads supporting methylated and not methylated states.
select_sites_with_good_coverage.R selects sites which are present in all samples of interest (which will be used to construct DNAm clock). Coverage is set to be 5 or greater in at least 90% of the samples.
combine_metlev.R makes a dataframe of methylation levels for the sites selected using select_sites_with_good_coverage.R
Making_WLMT.py was used to create a whole lifespan mouse multi-tissue DNA methylation clock base on DNA methylation level dataframes created in the previous scripts.