pkg <- read.dcf("../DESCRIPTION", fields = "Package")[1] library(pkg, character.only = TRUE)
library(`r pkg`)
echoannot
includes data generated by
"Nott2019":
Nott A, Holtman IR, Coufal NG, ... Glass CK. Brain cell type-specific enhancer-promoter interactome maps and disease-risk association. Science. 2019 Nov 29;366(6469):1134-1139. doi: 10.1126/science.aay0793. Epub 2019 Nov 14. PMID: 31727856; PMCID: PMC7028213.
superenhancers <- echoannot::get_NOTT2019_superenhancer_interactome() enhancers_promoters <- echoannot::NOTT2019_get_promoter_interactome_data() peaks <- echoannot::NOTT2019_get_epigenomic_peaks()
dat <- echodata::BST1 histo_out <- echoannot::NOTT2019_epigenomic_histograms(dat = dat)
In addition to the plot object, tables of both raw read ranges and called peaks are included in the output list.
knitr::kable(head(histo_out$data$raw)) knitr::kable(head(histo_out$data$peaks))
echoannot
also includes data generated by
"Corces2019":
Corces, M.R., Shcherbina, A., Kundu, S. et al. Single-cell epigenomic analyses implicate candidate causal variants at inherited risk loci for Alzheimer’s and Parkinson’s diseases. Nat Genet 52, 1158–1168 (2020). https://doi.org/10.1038/s41588-020-00721-x
bulkATACseq_peaks <- echoannot::get_CORCES2020_bulkATACseq_peaks() cicero_coaccessibility <- echoannot::get_CORCES2020_cicero_coaccessibility() hichip_fithichip_loop_calls <- echoannot::get_CORCES2020_hichip_fithichip_loop_calls() scATACseq_celltype_peaks <- echoannot::get_CORCES2020_scATACseq_celltype_peaks() scATACseq_peaks <- echoannot::get_CORCES2020_scATACseq_peaks()
peak_dat <- echoannot::granges_overlap( dat1 = dat, chrom_col.1 = "CHR", start_col.1 = "POS", dat2 = scATACseq_celltype_peaks, chrom_col.2 = "hg38_Chromosome", start_col.2 = "hg38_Start", end_col.2 = "hg38_Stop") ggbio::autoplot(peak_dat, ggplot2::aes(y=ExcitatoryNeurons, color=Effect))
utils::sessionInfo()
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