Plot annotation peaks: ROADMAP

Source: R/ROADMAP_plot.R

Import annotation from ROADMAP, filter to only those within the range of dat, and then plot the peaks. If the annotation has already been downloaded previously, it will be reused.

ROADMAP_plot(
  dat,
  roadmap_query,
  lib_name = "Roadmap.ChromatinMarks_CellTypes",
  locus_dir = tempdir(),
  limit_files = NULL,
  n_top = 5,
  adjust = 0.2,
  force_new = FALSE,
  show_plot = FALSE,
  conda_env = "echoR_mini",
  nThread = 1,
  verbose = TRUE
)

Arguments

dat

data.table with at least the following columns:

SNP

SNP RSID

CHR

chromosome

POS

position

roadmap_query

Search all columns in the Roadmap annotations metadata and only query annotations that contain your keywords. Can provide multiple keywords in list form: c("placenta","liver","monocytes")

lib_name

Name of the data library to use.

locus_dir

Locus-specific directory.

limit_files

Limit the number of annotation files queried (for faster testing).

n_top

Number of top annotations to be plotted (passed to ROADMAP_query).

adjust

The granularity of the peaks.

force_new

Download and prepare a new query even if the file already exists locally (Default: FALSE).

show_plot

Print the plot.

conda_env

Conda environment to search for tabix in.

nThread

Number of threads to parallelise downloading annotations over.

verbose

Print messages.

Value

A named list containing:

  • "data"GRanges object within the queried coordinates.

  • "plot"ggbio plot.

Examples

dat <- echodata::BST1[seq_len(1000),]
roadmap_out <- echoplot::ROADMAP_plot(
    dat = dat,
    roadmap_query = "monocyte")
#> echoannot:: Plotting ROADMAP annotations.
#> Converting dat to GRanges object.
#> + ROADMAP:: 2 annotation(s) identified that match: monocyte
#> Constructing GRanges query using min/max ranges across one or more chromosomes.
#> + as_blocks=TRUE: Will query a single range per chromosome that covers all regions requested (plus anything in between).
#> Downloading Roadmap Chromatin Marks: E124
#> Converting dat to GRanges object.
#> Saving query ==> /tmp/Rtmp6PJhbO/roadmap_query--monocyte.n_top--5.limit_files--./ROADMAP_query.E124.rds
#> Converting 1 GRanges object to separate BED files.
#> Saving BED file ==> /tmp/Rtmp6PJhbO/roadmap_query--monocyte.n_top--5.limit_files--./E124.bed.txt.gz
#> BED subset downloaded in 11.075 seconds
#> Constructing GRanges query using min/max ranges across one or more chromosomes.
#> + as_blocks=TRUE: Will query a single range per chromosome that covers all regions requested (plus anything in between).
#> Downloading Roadmap Chromatin Marks: E029
#> Converting dat to GRanges object.
#> Saving query ==> /tmp/Rtmp6PJhbO/roadmap_query--monocyte.n_top--5.limit_files--./ROADMAP_query.E029.rds
#> Converting 1 GRanges object to separate BED files.
#> Saving BED file ==> /tmp/Rtmp6PJhbO/roadmap_query--monocyte.n_top--5.limit_files--./E029.bed.txt.gz
#> BED subset downloaded in 8.809 seconds
#> ROADMAP:: Annotating GRangesList.
#> Annotating chromatin states.
#> Merging and processing ROADMAP annotations.
#> ROADMAP:: Done in 0.43 min.
#> Generating ROADMAP track plot.
#> Warning: Ignoring unknown parameters: `facets`
#> Warning: no non-missing arguments to max; returning -Inf