A docker image for single-cell analyses. It's on docker-hub and GitHub. This repository is an update of singlecell_jupyter.
-
2022.11.16
- Rename to ShortCake 🍰
-
2022.08.2 (2022-08)
- Create separate environments for python tools to avoid version conflict. They can be executed from Jupyter notebook
-
2022.03 (2022-03-03)
- Separate Dockerfile to Dockerfile.R and Dockerfile.Python
- change base image from
pytorch-1.5-cuda10.1-cudnn7-devel
tonvidia/cuda:11.5.1-cudnn8-devel-ubuntu20.04
to upgrade Python to 3.9 - Add CellChat, dyngen, Dynamo
-
2021.03 (2021-05-01):
- Add datasets in SeuratData
- Add Pagoda2
-
2021.02 (2021-02-07):
- Add programs
- Use pip venv for several tools to avoid package conflicts (e.g., tensorflow)
-
2020.12 (2020-12-24):
- Add
docker-compose.yml
to allow GitHub Token - Omit the password to login Jupyter notebook
- Add programs
- Fix several bugs in the installation
- Add
-
v1.3.0 (2020-07-14): add programs
-
v1.2.0: change base image from
Ubuntu18.04
topytorch-1.5-cuda10.1-cudnn7-devel
to allow GPU computing -
v1.1.0: change base image
jupyter/datascience-notebook
toUbuntu18.04
-
Pipeline: Seurat (and wrappers), scater, scran, scanpy, scVI, monet, Pagoda2, kallisto (bustools)
-
Doublet finding: Scrublet, DoubletFinder
-
Batch correction and data integration: Harmony, scmap, scBio, SingleCellNet
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Clustering: SC3, metacell, SCCAF, Constclust, bigSCale2
-
Cluster annotation: RCA, CellAssign, garnett, scCatch, SingleR
-
Trajectory analysis: Monocle2/3, slingshot, Palantir, FROWMAP
-
RNA velocity: velocyto, scVelo, CellRank, Dynamo
-
Gene network: WGCNA, SCENIC (pySCENIC)
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Cell-to-cell interaction: CellPhoneDB, SingleCellSingnalR, scTensor, cell2cell, CellChat
-
Data imputation: scImpute, MAGIC, SAVER, SAVER-X, SCRABBLE
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Multi-modal: LIGER, scAI, MOFA2
-
Bulk deconvolution: SCDC, MuSiC
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Simulation: Splatter, dyngen
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Others: scGen, sleepwalk, singleCellHaystack, ComplexHeatmap
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scATAC-seq: cicero, chromVAR, ArchR, Signac, cisTopic, episcanpy
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Database (genome): BSgenome.Hsapiens.UCSC.hg19, BSgenome.Hsapiens.UCSC.hg38, BSgenome.Mmusculus.UCSC.mm10, BSgenome.Scerevisiae.UCSC.sacCer3, BSgenome.Dmelanogaster.UCSC.dm6
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Database (gene): EnsDb.Hsapiens.v75, EnsDb.Hsapiens.v79, EnsDb.Hsapiens.v86, EnsDb.Mmusculus.v79
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Database (motif): JASPAR2016, JASPAR2018, JASPAR2020
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SeuratData: ifnb_3.1.0, panc8_3.0.2, pbmcsca_3.0.0, pbmc3k_3.1.4, celegans.embryo_0.1.0, cbmc_3.1.4, hcabm40k_3.0.0, thp1.eccite_3.1.5, stxBrain_0.1.1, stxKidney_0.1.0, bmcite_0.3.0, pbmcMultiome_0.1.2, ssHippo_3.1.4
For Docker:
# pull docker image
docker pull rnakato/shortcake
# container login
docker run [--gpus all] --rm -it rnakato/shortcake /bin/bash
# jupyter notebook (see 'mnt/' directory in the notebook )
docker run [--gpus all] --rm -p 8888:8888 -v (your directory):/work/mnt rnakato/shortcake jupyternotebook.sh
For Singularity:
# build image
singularity build -F shortcake.sif docker://rnakato/shortcake
# jupyter notebook
singularity exec [--nv] shortcake.sif jupyternotebook.sh
# execute R directory
singularity exec [--nv] shortcake.sif R
First clone and move to the repository
git clone https://github.com/rnakato/ShortCake
cd ShortCake
- Because the Dockerfile installs many packages from GitHub, first get a GitHub token from your own repository and add it in
Docker_R/docker-compose.R.yml
andDocker_Python/docker-compose.yml
. - Download the dataset of SeuratData from our GoogleDrive and unzip it in
Docker_R
directory.
Then build packages:
# build R packages
cd Docker_R
docker-compose -f docker-compose.R.yml build
# Then build Python packages
cd ../Docker_Python/
docker-compose -f docker-compose.yml build
Ryuichiro Nakato: rnakato AT iqb.u-tokyo.ac.jp