SNPs.CommonSingle.RdSNP annotation from various versions of dbSNP as represented on UCSC Common SNP table. Overlap is based on genomic mappings from the annotation package.
An object of class DataFrame. Rownames are CpG identifiers.
There are 6 columns Probe_rs, Probe_maf, CpG_rs,
CpG_maf, SBE_rs, and SBE_maf. ‘Probe’
indicates a SNP in the probe, ‘CpG’ a SNP in the CpG site and
‘SBE’ in the single base extension site. The _rs gives
the SNP RS identifier and the _maf gives the minor allele frequency.
In addition to the SNP information provided by Illumina, we have added
independent information on the overlap of the EPIC (v2.0) array with various
versions of dbSNP. The overlap is based on the
mappings of the array to the hg38 genome provided by Illumina. As
dbSNP we have used the ‘Common’ table from UCSC
(ie. ‘snp151Common’). This track contains variants from dbSNP
which have a minor allele frequency (MAF) of greater than 1 percent
(specifically, this requires dbSNP to actually contain MAF
information). Furthermore, we only kept variants marked as
‘single’ (ie. standard single nucleotide changes, but not
insertions or deletions). Scripts for retrieving the UCSC dbSNP table
and doing the overlap are contained in the scripts directory.
The variants are described in 6 different columns. Probe_rs
tells us the RS number (SNP ID number) for a SNP overlapping the
probe, and Probe_maf is the minor allelle frequency for the SNP
(in case multiple SNPs overlap, only one is recorded). Similarly,
CpG_rs describe SNPs overlapping the CpG site and SBE_rs
the single base extension of the measured methylation loci.
UCSC Common SNP Table.
SNPs.141CommonSingle
#> DataFrame with 930075 rows and 6 columns
#> Probe_rs Probe_maf CpG_rs CpG_maf SBE_rs
#> <character> <numeric> <character> <numeric> <character>
#> cg25324105_BC11 NA NA NA NA NA
#> cg25383568_TC11 NA NA NA NA NA
#> cg25455143_BC11 NA NA NA NA NA
#> cg25459778_BC11 NA NA NA NA NA
#> cg25487775_BC11 NA NA NA NA NA
#> ... ... ... ... ... ...
#> ch.22.16108507R_BC21 rs5748987 0.257091 NA NA NA
#> ch.22.40657F_BC21 NA NA NA NA NA
#> ch.22.78028F_BC21 NA NA NA NA NA
#> ch.22.17803970R_BC21 NA NA NA NA NA
#> ch.22.107403R_TC21 NA NA NA NA NA
#> SBE_maf
#> <numeric>
#> cg25324105_BC11 NA
#> cg25383568_TC11 NA
#> cg25455143_BC11 NA
#> cg25459778_BC11 NA
#> cg25487775_BC11 NA
#> ... ...
#> ch.22.16108507R_BC21 NA
#> ch.22.40657F_BC21 NA
#> ch.22.78028F_BC21 NA
#> ch.22.17803970R_BC21 NA
#> ch.22.107403R_TC21 NA
SNPs.142CommonSingle
#> DataFrame with 930075 rows and 6 columns
#> Probe_rs Probe_maf CpG_rs CpG_maf SBE_rs
#> <character> <numeric> <character> <numeric> <character>
#> cg25324105_BC11 NA NA NA NA NA
#> cg25383568_TC11 NA NA NA NA NA
#> cg25455143_BC11 NA NA NA NA NA
#> cg25459778_BC11 NA NA NA NA NA
#> cg25487775_BC11 NA NA NA NA NA
#> ... ... ... ... ... ...
#> ch.22.16108507R_BC21 rs5748987 0.250799 NA NA NA
#> ch.22.40657F_BC21 rs143942158 0.015575 NA NA NA
#> ch.22.78028F_BC21 NA NA NA NA NA
#> ch.22.17803970R_BC21 NA NA NA NA NA
#> ch.22.107403R_TC21 NA NA NA NA NA
#> SBE_maf
#> <numeric>
#> cg25324105_BC11 NA
#> cg25383568_TC11 NA
#> cg25455143_BC11 NA
#> cg25459778_BC11 NA
#> cg25487775_BC11 NA
#> ... ...
#> ch.22.16108507R_BC21 NA
#> ch.22.40657F_BC21 NA
#> ch.22.78028F_BC21 NA
#> ch.22.17803970R_BC21 NA
#> ch.22.107403R_TC21 NA
SNPs.144CommonSingle
#> DataFrame with 930075 rows and 6 columns
#> Probe_rs Probe_maf CpG_rs CpG_maf SBE_rs
#> <character> <numeric> <character> <numeric> <character>
#> cg25324105_BC11 NA NA NA NA NA
#> cg25383568_TC11 NA NA NA NA NA
#> cg25455143_BC11 NA NA NA NA NA
#> cg25459778_BC11 NA NA NA NA NA
#> cg25487775_BC11 NA NA NA NA NA
#> ... ... ... ... ... ...
#> ch.22.16108507R_BC21 rs5748987 0.250799 NA NA NA
#> ch.22.40657F_BC21 rs143942158 0.015575 NA NA NA
#> ch.22.78028F_BC21 NA NA NA NA NA
#> ch.22.17803970R_BC21 NA NA NA NA NA
#> ch.22.107403R_TC21 NA NA NA NA NA
#> SBE_maf
#> <numeric>
#> cg25324105_BC11 NA
#> cg25383568_TC11 NA
#> cg25455143_BC11 NA
#> cg25459778_BC11 NA
#> cg25487775_BC11 NA
#> ... ...
#> ch.22.16108507R_BC21 NA
#> ch.22.40657F_BC21 NA
#> ch.22.78028F_BC21 NA
#> ch.22.17803970R_BC21 NA
#> ch.22.107403R_TC21 NA
SNPs.146CommonSingle
#> DataFrame with 930075 rows and 6 columns
#> Probe_rs Probe_maf CpG_rs CpG_maf SBE_rs
#> <character> <numeric> <character> <numeric> <character>
#> cg25324105_BC11 NA NA NA NA NA
#> cg25383568_TC11 NA NA NA NA NA
#> cg25455143_BC11 NA NA NA NA NA
#> cg25459778_BC11 NA NA NA NA NA
#> cg25487775_BC11 NA NA NA NA NA
#> ... ... ... ... ... ...
#> ch.22.16108507R_BC21 rs5748987 0.250799 NA NA NA
#> ch.22.40657F_BC21 rs143942158 0.015575 NA NA NA
#> ch.22.78028F_BC21 NA NA NA NA NA
#> ch.22.17803970R_BC21 NA NA NA NA NA
#> ch.22.107403R_TC21 NA NA NA NA NA
#> SBE_maf
#> <numeric>
#> cg25324105_BC11 NA
#> cg25383568_TC11 NA
#> cg25455143_BC11 NA
#> cg25459778_BC11 NA
#> cg25487775_BC11 NA
#> ... ...
#> ch.22.16108507R_BC21 NA
#> ch.22.40657F_BC21 NA
#> ch.22.78028F_BC21 NA
#> ch.22.17803970R_BC21 NA
#> ch.22.107403R_TC21 NA
SNPs.147CommonSingle
#> DataFrame with 930075 rows and 6 columns
#> Probe_rs Probe_maf CpG_rs CpG_maf SBE_rs
#> <character> <numeric> <character> <numeric> <character>
#> cg25324105_BC11 NA NA NA NA NA
#> cg25383568_TC11 NA NA NA NA NA
#> cg25455143_BC11 NA NA NA NA NA
#> cg25459778_BC11 NA NA NA NA NA
#> cg25487775_BC11 NA NA NA NA NA
#> ... ... ... ... ... ...
#> ch.22.16108507R_BC21 rs5748987 0.250799 NA NA NA
#> ch.22.40657F_BC21 rs143942158 0.015575 NA NA NA
#> ch.22.78028F_BC21 NA NA NA NA NA
#> ch.22.17803970R_BC21 NA NA NA NA NA
#> ch.22.107403R_TC21 NA NA NA NA NA
#> SBE_maf
#> <numeric>
#> cg25324105_BC11 NA
#> cg25383568_TC11 NA
#> cg25455143_BC11 NA
#> cg25459778_BC11 NA
#> cg25487775_BC11 NA
#> ... ...
#> ch.22.16108507R_BC21 NA
#> ch.22.40657F_BC21 NA
#> ch.22.78028F_BC21 NA
#> ch.22.17803970R_BC21 NA
#> ch.22.107403R_TC21 NA
SNPs.150CommonSingle
#> DataFrame with 930075 rows and 6 columns
#> Probe_rs Probe_maf CpG_rs CpG_maf SBE_rs
#> <character> <numeric> <character> <numeric> <character>
#> cg25324105_BC11 NA NA NA NA NA
#> cg25383568_TC11 NA NA NA NA NA
#> cg25455143_BC11 NA NA NA NA NA
#> cg25459778_BC11 NA NA NA NA NA
#> cg25487775_BC11 NA NA NA NA NA
#> ... ... ... ... ... ...
#> ch.22.16108507R_BC21 rs5748987 0.250799 NA NA NA
#> ch.22.40657F_BC21 rs143942158 0.015575 NA NA NA
#> ch.22.78028F_BC21 NA NA NA NA NA
#> ch.22.17803970R_BC21 NA NA NA NA NA
#> ch.22.107403R_TC21 NA NA NA NA NA
#> SBE_maf
#> <numeric>
#> cg25324105_BC11 NA
#> cg25383568_TC11 NA
#> cg25455143_BC11 NA
#> cg25459778_BC11 NA
#> cg25487775_BC11 NA
#> ... ...
#> ch.22.16108507R_BC21 NA
#> ch.22.40657F_BC21 NA
#> ch.22.78028F_BC21 NA
#> ch.22.17803970R_BC21 NA
#> ch.22.107403R_TC21 NA
SNPs.151CommonSingle
#> DataFrame with 930075 rows and 6 columns
#> Probe_rs Probe_maf CpG_rs CpG_maf SBE_rs
#> <character> <numeric> <character> <numeric> <character>
#> cg25324105_BC11 NA NA NA NA NA
#> cg25383568_TC11 NA NA NA NA NA
#> cg25455143_BC11 NA NA NA NA NA
#> cg25459778_BC11 NA NA NA NA NA
#> cg25487775_BC11 NA NA NA NA NA
#> ... ... ... ... ... ...
#> ch.22.16108507R_BC21 rs5748987 0.250799 NA NA NA
#> ch.22.40657F_BC21 rs143942158 0.015575 NA NA NA
#> ch.22.78028F_BC21 NA NA NA NA NA
#> ch.22.17803970R_BC21 NA NA NA NA NA
#> ch.22.107403R_TC21 NA NA NA NA NA
#> SBE_maf
#> <numeric>
#> cg25324105_BC11 NA
#> cg25383568_TC11 NA
#> cg25455143_BC11 NA
#> cg25459778_BC11 NA
#> cg25487775_BC11 NA
#> ... ...
#> ch.22.16108507R_BC21 NA
#> ch.22.40657F_BC21 NA
#> ch.22.78028F_BC21 NA
#> ch.22.17803970R_BC21 NA
#> ch.22.107403R_TC21 NA