Add Liu and Zhou's 2021 mouse brain data

[imallona]

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• Prototype: NA-agnostic, CpN methylation calling caution the references are fully disregarded here

Cell partitions

Using the harmonized_ecker_metadata.tsv.gz generated with snakemake --use-conda --cores 1 ecker_data/harmonized_ecker_metadata.tsv.gz :

$ zcat harmonized_ecker_metadata.tsv.gz | cut -f14-15 | sort | uniq -c |  sed 's/^ *//g' | sort -V
1 "CellClass"   "MajorType"
1 "Inh" "MSN-D2"
1 "NonN"        "ANP"
3 "Inh" "Unc5c"
5 "NonN"        "EC"
7 "Inh" "PAL-Inh"
18 "NonN"       "PC"
24 "NonN"       "VLMC-Pia"
27 "NonN"       "OPC"
32 "Exc"        "CLA"
37 "NonN"       "VLMC"
59 "NonN"       "MGC"
107 "NonN"      "ASC"
120 "Exc"       "L6b"
145 "NonN"      "ODC"
271 "Exc"       "NP-L6"
288 "Inh"       "CGE-Vip"
319 NA  NA
327 "Inh"       "CGE-Lamp5"
357 "Exc"       "PT-L5"
447 "Inh"       "MGE-Pvalb"
467 "Inh"       "MGE-Sst"
840 "Exc"       "IT-L6"
1064 "Exc"      "IT-L4"
1387 "Exc"      "IT-L5"
1632 "Exc"      "CT-L6"
1956 "Exc"      "IT-L23"

So a very rough first approach would be: Inhibitory neurons; Excitatory neurons; and all the NonNeurons separately, that is, the ANP, then the EC, then the VLMC`, etc. Perhaps with just 10 cells per group, when possible.

Regionsets

• Just nonoverlapping 10nt-long windows, to get a feeling of the overall methylation and entropy levels for CpN or CpH methylation.

Assembly

This is mm10.