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JBrowseR

JBrowseR renders a JBrowse 2 linear genome view, drawn on the GPU, as an htmlwidget. Embed a full genome browser in an R Markdown document or Shiny app, or launch one from the R console. It shares the same framework-agnostic view core as the Python anywidget, so both stay in step.

Install

# released
install.packages("JBrowseR")

# development
# install.packages("remotes")
remotes::install_github("GMOD/JBrowseR")

A declarative API

You describe the browser with plain values; helper constructors build the config.

Name a hosted genome and the assembly, reference-name aliases, cytobands, and gene-name search all come preconfigured, and location can be a gene symbol:

library(JBrowseR)

JBrowseR("hg38", location = "BRCA1")

Add tracks by URL. The track type and index files (.bai/.crai/.tbi) are inferred from the extension:

JBrowseR(
  "hg38",
  tracks = tracks(
    track(
      "https://jbrowse.org/genomes/GRCh38/alignments/NA12878/NA12878.alt_bwamem_GRCh38DH.20150826.CEU.exome.cram",
      name = "NA12878 Exome"
    )
  ),
  location = "17:43,044,295..43,048,000"
)

R adds what a config can't express itself: track_data_frame() turns an in-memory data frame into a track (no file, no server), and assembly() writes a little assembly boilerplate from a FASTA URL. For full control, hand a whole JBrowse config.json to JBrowseR(config = ...).

Comparing genomes

JBrowseR() shows a single linear genome view. JBrowseRApp() drives the full app from a declarative views list, where each entry can be a linear_view(), a synteny_view(), or a dotplot_view(), so a comparative figure (several genomes stacked with the blocks each pair shares drawn between the rows, or a whole-genome dotplot) is one call:

JBrowseRApp(
  assemblies = list(assembly(hg38_fa), assembly(mm39_fa)),
  tracks = list(synteny_track(paf_url, "hg38", "mm39", track_id = "hg38-mm39")),
  views = list(synteny_view(c("hg38", "mm39"), tracks = "hg38-mm39"))
)

The comparative-synteny vignette walks through four E. coli strains from one all-vs-all alignment, the same hosted data as the all-vs-all synteny tutorial.

Reacting to clicks in Shiny

Rendered inside Shiny, clicking a feature sets input$selectedFeature to the feature's data, so tables, plots, and links can follow the current selection. Use JBrowseROutput() in the UI and renderJBrowseR() on the server.

Run in Colab

A runnable R-runtime Colab notebook walks through the one-line genome, alignments, an R data-frame track, and cancer structural variants.

Full documentation is at gmod.github.io/JBrowseR.

See also