echoannot
: Functions for annotating genomic datawith annotations and epigenomic data.
This R package is part of the echoverse suite that supports
echolocatoR
: an automated
genomic fine-mapping pipeline.
If you use echoannot
, please cite:
if(!require("remotes")) install.packages("remotes")
remotes::install_github("RajLabMSSM/echoannot")
library(echoannot)
For more detailed information about each dataset, use ?
:
R library(echolocatoR) ?NOTT_2019.interactome # example dataset
Data from this publication contains results from cell type-specific (neurons, oligodendrocytes, astrocytes, microglia, & peripheral myeloid cells) epigenomic assays (H3K27ac, ATAC, H3K4me3) from human brain tissue.
For detailed metadata, see:
r
data("NOTT_2019.bigwig_metadata")
Built-in datasets:
Enhancer/promoter coordinates (as GenomicRanges)
r
data("NOTT_2019.interactome")
# Examples of the data nested in "NOTT_2019.interactome" object:
NOTT_2019.interactome$`Neuronal promoters`
NOTT_2019.interactome$`Neuronal enhancers`
NOTT_2019.interactome$`Microglia promoters`
NOTT_2019.interactome$`Microglia enhancers`
...
...
r
NOTT_2019.interactome$H3K4me3_around_TSS_annotated_pe
NOTT_2019.interactome$`Microglia interactome`
NOTT_2019.interactome$`Neuronal interactome`
NOTT_2019.interactome$`Oligo interactome`
...
...
API access to full bigWig files on UCSC Genome Browser, which includes
Epigenomic reads (as GenomicRanges)
r
data("CORCES_2020.bulkATACseq_peaks")
data("CORCES_2020.cicero_coaccessibility")
data("CORCES_2020.HiChIP_FitHiChIP_loop_calls")
data("CORCES_2020.scATACseq_celltype_peaks")
data("CORCES_2020.scATACseq_peaks")
Brian M. Schilder, Bioinformatician II Raj Lab Department of Neuroscience, Icahn School of Medicine at Mount Sinai
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