After configuring a Vitessce widget, you may want to obtain the static files associated and deploy the same Vitessce configuration as a static website. This page demonstrates this process for an example dataset from SeuratData.
First, install the dependencies:
install.packages("devtools")
devtools::install_github("satijalab/seurat-data")
devtools::install_github("vitessce/vitessceAnalysisR")
Create the Vitessce configuration:
library(vitessceR)
library(vitessceAnalysisR)
library(SeuratData)
SeuratData::InstallData("pbmc3k")
data("pbmc3k.final")
force(pbmc3k.final)
adata_path <- file.path("data", "seurat", "pbmc3k.final.h5ad.zarr")
vitessceAnalysisR::seurat_to_anndata_zarr(pbmc3k.final, adata_path)
vc <- VitessceConfig$new(schema_version = "1.0.16", name = "My config")
dataset <- vc$add_dataset("My dataset")
dataset <- dataset$add_object(
AnnDataWrapper$new(
adata_path=adata_path,
obs_embedding_paths = c("obsm/X_pca", "obsm/X_umap"),
obs_embedding_names = c("PCA", "UMAP"),
obs_set_paths = c("obs/seurat_annotations", "obs/seurat_clusters")
)
)
scatterplot <- vc$add_view(dataset, Component$SCATTERPLOT, mapping = "PCA")
vc$layout(scatterplot)
Export files for serving locally
Run the export
function on the VitessceConfig
. Specify the directory in which to store the exported files with out_dir
.
vc$export(out_dir = "./my_vitessce_files")
The directory ./my_vitessce_files
should now contain three files:
cells.json
cell-sets.json
clusters.json
Serve the exported files
Now that the files have been saved to the ./my_vitessce_files
directory, they can be served by any static web server.
If you would like to serve the files locally, we recommend http-server which can be installed with NPM or Homebrew:
http-server ./my_vitessce_files/ --cors -p 3000
Export files for serving from AWS S3
Rather than serving the data files locally, you may want to upload the files to a remote static file hosting service such as AWS S3, allowing the Vitessce URL to be shared with others. Visit our data hosting documentation page to learn more about configuring file hosting services for use with Vitessce. Install the AWS S3 command-line interface by following the instructions here.
Confirm that the CLI has been installed:
aws --version
Configure the AWS CLI by using any of the configuration methods, such as the environment variable method.
In the case of AWS S3, you know ahead of time that the data files will ultimately be served from your S3 bucket, so you can include the base_url
and with_config = TRUE
parameters when calling the export function. For instance, if you intend to upload the files to an AWS S3 bucket called my_bucket
:
vc$export(with_config = TRUE, base_url = "https://my_bucket.s3.amazonaws.com", out_dir = "./my_vitessce_files")
The directory ./my_vitessce_files
should now contain the three data files, plus the view config as a JSON file (config.json
):
cells.json
cell-sets.json
clusters.json
-
config.json
(the file URLs in this config will include thebase_url
for the bucket)
Upload exported files to S3
Upload all four files to your bucket:
aws s3 cp --recursive ./my_vitessce_files s3://my_bucket
In this case, rather than including the configuration as url-encoded JSON in the URL, you can simply point to the configuration JSON file in the bucket:
http://vitessce.io/?url=https://my_bucket.s3.amazonaws.com/config.json