Cicero_coaccessibility from human brain tissue

Cicero coaccessibility analysis for peaks that overlap SNPs derived from analysis of scATAC-seq data. Each row represents an individual peak identified from the feature binarization analysis (see methods).

get_CORCES2020_cicero_coaccessibility()

Source

https://doi.org/10.1038/s41588-020-00721-x

Details

Data originally from Corces et al. (bioRxiv), as of May 2020. Specifically: STable10_Coacessibility_Peak_loop_connection, Cicero Coaccessibility sheet. Peak_ID_Peak1 - A unique number that identifies the peak across supplementary tables.

Column dictionary:

hg38_Chromosome_Peak1

The hg38 chromosome of the first loop Peak.

hg38_Start_Peak1

The hg38 start position of the first loop Peak.

hg38_Stop_Peak1

The hg38 stop position of the first loop Peak.

Width_Peak1

The width of the first loop Peak.

Peak_ID_Peak2

A unique number that identifies the peak across supplementary tables.

hg38_Chromosome_Peak2

The hg38 chromosome of the second loop Peak.

hg38_Start_Peak2

The hg38 start position of the second loop Peak.

hg38_Stop_Peak2

The hg38 stop position of the second loop Peak.

Width_Peak2

The width of the second loop Peak.

Coaccessibility

The coaccessibility correlation for the given peak pair.

Peak1_hasSNP

A boolean variable determining whether the first peak overlaps a SNP from our AD/PD GWAS analyses.

Peak2_hasSNP

A boolean variable determining whether the second peak overlaps a SNP from our AD/PD GWAS analyses.

See also

Other CORCES2020: CORCES2020_get_ATAC_peak_overlap(), CORCES2020_get_hichip_fithichip_overlap(), CORCES2020_prepare_bulkATAC_peak_overlap(), CORCES2020_prepare_scATAC_peak_overlap(), get_CORCES2020_bulkATACseq_peaks(), get_CORCES2020_hichip_fithichip_loop_calls(), get_CORCES2020_scATACseq_celltype_peaks(), get_CORCES2020_scATACseq_peaks()

Examples

if (FALSE) {
dat <- readxl::read_excel(
    file.path(
        "~/Desktop/Fine_Mapping/echolocatoR/annotations",
        "Coceres_2020/STable10_Coacessibility_Peak_loop_connection.xlsx"
    ),
    skip = 21, sheet = 2
)
CORCES2020_cicero_coaccessibility <- data.table::data.table(dat)

#### piggyback ####
tmp <- file.path(tempdir(), "CORCES2020_cicero_coaccessibility.tsv.gz")
data.table::fwrite(CORCES2020_cicero_coaccessibility, tmp, sep = "\t")
piggyback::pb_upload(
    file = tmp,
    repo = "RajLabMSSM/echoannot"
)
}