Notebook
python fetchdata.py -d "[sr320@washington.edu].[BiGo_methratio_GFF_boop]​" -f tsv -o /Volumes/web/cnidarian/BiGo_methratio_boop.gff
#CG count per promoter !intersectbed -c -a /Volumes/web/cnidarian/TJGR_prom_subtract_gene1.gff -b /Volumes/web/trilobite/Crassostrea_gigas_v9_tracks/Cgigas_v9_CG.gff > /Volumes/web/cnidarian/TJGR_prom_subgene_CGcount.txt
#mCg per promoter !intersectbed -c -a /Volumes/web/cnidarian/TJGR_prom_subtract_gene1.gff -b /Volumes/web/cnidarian/BiGo_methratio_mCG_tail.gff > /Volumes/web/cnidarian/BiGo_prom_subgene_CGcount.txt
Given that only "promoters" with islands are examined - an absolute methylation approach could be used