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The UCSC Cell Browser is a web application for interactive exploration of single-cell datasets, supporting expression queries, dimensionality reduction plots, cluster annotations, and marker gene tables. ExportToCellbrowser() converts a Seurat object into the file format expected by Cell Browser, and can optionally build and launch a local Cell Browser instance.
Source: UCSC Cell BrowserAuthors: Maximilian Haeussler, Nikolay Markov, Brian Raney, and Lucas Seninge

​
Installation

Cell Browser is a Python package and must be installed separately from SeuratWrappers: 
# System-wide
sudo pip install cellbrowser

# User-local (no root required)
pip install cellbrowser --user
SeuratWrappers accesses Cell Browser through R’s reticulate package. Make sure R’s reticulate is pointed at the Python environment where cellbrowser is installed. 
# Verify reticulate can find the cellbrowser module
reticulate::py_module_available("cellbrowser")

​
Key Functions

  • ExportToCellbrowser() — Exports a Seurat object to a directory of Cell Browser input files. Optionally builds the static website and starts a local web server.
  • StopCellbrowser() — Stops a running Cell Browser web server launched from R.

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How It Works

ExportToCellbrowser() writes the following files to the output directory:
  • exprMatrix.tsv.gz (or matrix.mtx.gz for large matrices) — expression matrix
  • <reduction>.coords.tsv — cell embeddings for each requested reduction
  • meta.tsv — cell metadata
  • markers.tsv — cluster marker genes (computed or user-supplied)
  • cellbrowser.conf — auto-generated Cell Browser configuration file
If cb.dir is specified, the function additionally runs cbBuild to produce a static HTML/JSON website. If port is also set, a local web server is started and the browser is opened automatically.

​
ExportToCellbrowser Parameters

​
object
Seurat object
required
The Seurat object to export.
​
dir
character
required
Output directory for the exported Cell Browser input files. Created if it does not exist.
​
dataset.name
character
default:"Project(object)"
Name for the dataset in the Cell Browser UI. Defaults to the Seurat project name.
​
reductions
character vector
default:"NULL"
Names of reductions to export. If NULL, all reductions present in the object are exported. Only the first two dimensions of each reduction are used.
​
markers.file
character
default:"NULL"
Path to a pre-computed marker gene file to include. If NULL and skip.markers = FALSE, markers are looked up in object@misc$markers or computed with FindAllMarkers.
​
markers.n
integer
default:"100"
Number of top markers per cluster to include when computing markers automatically.
​
matrix.slot
character
default:"counts"
Which expression matrix to export. Options: "counts", "data", "scale.data".
​
use.mtx
logical
default:"FALSE"
Export the matrix in .mtx.gz format instead of TSV. Automatically enabled for matrices that exceed R’s maximum dense matrix size.
​
cluster.field
character
default:"Cluster"
Name of the metadata field containing cluster assignments.
​
cb.dir
character
default:"NULL"
Directory where the Cell Browser static website (HTML/JSON) should be built. Requires cellbrowser to be available via reticulate.
​
port
integer
default:"NULL"
Port on which to start the Cell Browser web server after export. Requires cb.dir to be set.
​
meta.fields
character vector
default:"NULL"
Metadata columns to include. Defaults to all columns.
​
meta.fields.names
character vector
default:"NULL"
Human-readable display names for the exported metadata fields. Must be the same length as meta.fields.
​
skip.markers
logical
default:"FALSE"
If TRUE, skip marker gene export entirely.
​
skip.expr.matrix
logical
default:"FALSE"
If TRUE, skip exporting the expression matrix.
​
skip.metadata
logical
default:"FALSE"
If TRUE, skip exporting cell metadata.
​
skip.reductions
logical
default:"FALSE"
If TRUE, skip exporting dimensionality reduction coordinates.

​
Workflow

1

Load libraries and data

library(Seurat)
library(SeuratData)
library(SeuratWrappers)

InstallData("pbmc3k")
pbmc3k <- LoadData("pbmc3k", type = "pbmc3k.final")
2

Export to Cell Browser

Export the object, build the static website, and launch a local server:
ExportToCellbrowser(
  pbmc3k,
  dir = "out",
  cb.dir = "cb_out",
  port = 8080,
  reductions = "umap"
)
This writes all input files to out/, builds the static website in cb_out/, and opens the Cell Browser at http://localhost:8080 in your default browser.
3

Stop the server when done

StopCellbrowser()

​
Export Without Launching a Server

To export files only without building the website or starting a server: 
ExportToCellbrowser(
  pbmc3k,
  dir = "out",
  dataset.name = "PBMC 3k"
)
The exported directory can then be built manually with the cbBuild command-line tool and copied to any web server.

​
Supplying Pre-Computed Markers

If you have already run FindAllMarkers, you can save the results and pass them in: 
markers <- FindAllMarkers(pbmc3k, only.pos = TRUE, logfc.threshold = 0.25)
write.table(markers, file = "markers.tsv", sep = "\t", quote = FALSE)

ExportToCellbrowser(
  pbmc3k,
  dir = "out",
  markers.file = "markers.tsv",
  dataset.name = "PBMC"
)
Alternatively, store markers in the object before exporting and they will be picked up automatically: 
pbmc3k@misc$markers <- FindAllMarkers(pbmc3k)
ExportToCellbrowser(pbmc3k, dir = "out", dataset.name = "PBMC")

​
Selecting Metadata Fields

Control which metadata columns appear in the Cell Browser UI: 
ExportToCellbrowser(
  pbmc3k,
  dir = "out",
  dataset.name = "PBMC",
  meta.fields = c("seurat_clusters", "seurat_annotations", "percent.mt"),
  meta.fields.names = c("Cluster", "Cell Type", "% Mitochondrial")
)

​
Python Environment Configuration

If reticulate cannot find the cellbrowser module, configure the Python environment explicitly before calling ExportToCellbrowser: 
library(reticulate)

# Point to a specific Python executable
use_python("/usr/local/bin/python3")

# Or activate a virtual environment
use_virtualenv("~/venvs/cellbrowser")

# Or use a conda environment
use_condaenv("cellbrowser")

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