Command Line

Launch

cirro launch [--backed] [--host HOST] [--markers [MARKERS [MARKERS ...]]] [--port PORT] [--no-open] [--spatial [SPATIAL [SPATIAL ...]]] dataset [dataset ...]

The launch command opens one or more datasets in h5ad, loom, or STAR-Fusion formats. Seurat objects can be loaded after converting to h5ad or loom formats (see vignette). Annotations and sets that are created are stored on disk in a JSON format.

Serve

cirro serve [--database DATABASE] [--db_uri DB_URI] [--email EMAIL] [--auth_client_id AUTH_CLIENT_ID] [-w WORKERS] [-t TIMEOUT] [-b BIND] [--footer FOOTER] [--header HEADER] [--upload UPLOAD]

Optional Arguments

db_uri

MongoDB database connection URI (default mongodb://localhost:27017/)

database

MongoDB database (default cirrocumulus)

email

Email address that server runs as

auth_client_id

OAuth client id

workers

The number of worker processes

bind

Server socket to bind. Server sockets can be any of $(HOST), $(HOST):$(PORT), fd://$(FD), or unix:$(PATH). An IP is a valid $(HOST). (default 127.0.0.1:5000)

footer

Markdown file to customize the application footer

upload

URL to allow users to upload files

header

Markdown file to customize the application header

The serve command starts the cirrocumulus server for use in a shared server environment which can handle concurrent requests from multiple users. The server can optionally enforce permissions at the dataset level, in order to securely share datasets with collaborators. Additionally, annotations and sets are created collaboratively among all users authorized to view a dataset and are stored in a database. The server can be deployed on a cloud VM, an on-premise machine, or on Google App Engine. When deployed in App Engine, the server can be configured to be use Google Cloud Firestore as a database. Please note that no datasets are available until you import a dataset into cirrocumulus.

Prepare Data

cirro prepare_data [--out OUT] [--backed] [--markers MARKERS] [--groups GROUPS] [--spatial SPATIAL] dataset

Positional Arguments

dataset

Path to dataset in h5ad, loom, or Seurat format.

Optional Arguments

spatial

Directory containing 10x visium spatial data (tissue_hires_image.png, scalefactors_json.json, and tissue_positions_list.csv) or a directory containing image.png, positions.image.csv with headers barcode, x, and y, and optionally diameter.image.txt containing spot diameter

markers

Path to JSON file that maps name to features. For example {“a”:[“gene1”, “gene2”], “b”:[“gene3”]}

backed

Load h5ad file in backed mode

groups

List of groups to compute markers for (e.g. louvain)

out

Path to output directory

The prepare_data command is used to freeze an h5ad, loom, or Seurat file in cirrocumulus format. The cirrocumulus format allows efficient partial dataset retrieval over a network (e.g. Google or S3 bucket) using limited memory.