Dec 17, 2021
Version 1.1 is now available.
- fixed incompatible issues related to the latest version of
pandas - fixed plotting issues related to the latest version of
matplotlibandseaborn
Jun 1, 2020
Version 1.0 is now available. The v1.0 has added a lot of new functionality:
- added QC metrics and plots
- added support of scATAC-seq analysis using peaks as features
- added support of interactive plots with plotly
- redesigned all plotting-related functions
- redesigned mapping procedure
- removed support of STREAM command line interface
See v1.0 for more details.
Jan 14, 2020
Version 0.4.1 is now available. We added support of feature top_pcs for Mapping
Nov 26, 2019
Version 0.4.0 is now available. Numerous changes have been introduced. Please check v0.4.0 for details.
STREAM (Single-cell Trajectories Reconstruction, Exploration And Mapping) is an interactive pipeline capable of disentangling and visualizing complex branching trajectories from both single-cell transcriptomic and epigenomic data.
STREAM is now published in Nature Communications! Please cite our paper Chen H, et al. Single-cell trajectories reconstruction, exploration and mapping of omics data with STREAM. Nature Communications, volume 10, Article number: 1903 (2019). if you find STREAM helpful for your research.
STREAM is written using the class anndata Wolf et al. Genome Biology (2018) and available as user-friendly open source software and can be used interactively as a web-application at stream.pinellolab.org, as a bioconda package https://bioconda.github.io/recipes/stream/README.html and as a standalone command-line tool with Docker https://github.com/pinellolab/STREAM
$ conda install -c bioconda streamIf you are new to conda environment:
-
If Anaconda (or miniconda) is already installed with Python 3, skip to 2) otherwise please download and install Python3 Anaconda from here: https://www.anaconda.com/download/
-
Open a terminal and add the Bioconda channel with the following commands:
$ conda config --add channels defaults
$ conda config --add channels bioconda
$ conda config --add channels conda-forge- Create an environment named
env_stream, install stream, jupyter, and activate it with the following commands:
- For single cell RNA-seq analysis:
$ conda create -n env_stream python=3.7 stream=1.0 jupyter
$ conda activate env_stream- For single cell ATAC-seq analysis:
$ conda create -n env_stream python=3.7 stream=1.0 stream_atac jupyter
$ conda activate env_stream- To perform STREAM analyis in Jupyter Notebook as shown in Tutorial, type
jupyter notebookwithinenv_stream:
$ jupyter notebookYou should see the notebook open in your browser.
-
Example for scRNA-seq: 1.1-STREAM_scRNA-seq (Bifurcation).ipynb
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Example for scRNA-seq: 1.2-STREAM_scRNA-seq (Multifurcation) on 2D visulization.ipynb
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Example for scRNA-seq: 1.3-STREAM_scRNA-seq (Multifurcation) on original embedding.ipynb
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Example for scATAC-seq(using peaks): 2.1-STREAM_scATAC-seq_peaks.ipynb
-
Example for scATAC-seq(using k-mers): 2.2-STREAM_scATAC-seq_k-mers.ipynb
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Example for scATAC-seq(using motifs): 2.3-STREAM_scATAC-seq_motifs.ipynb
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Example for mapping feature: 3-STREAM_mapping.ipynb
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Example for complex trajectories: 4-STREAM_complex_trajectories.ipynb
Tutorials for v0.4.1 and earlier versions can be found here
With Docker no installation is required, the only dependence is Docker itself. Users will completely get rid of all the installation and configuration issues. Docker will do all the dirty work for you!
Docker can be downloaded freely from here: https://store.docker.com/search?offering=community&type=edition
To get an image of STREAM, simply execute the following command:
$ docker pull pinellolab/streamBasic usage of docker run
$ docker run [OPTIONS] IMAGE [COMMAND] [ARG...]Options:
--publish , -p Publish a container’s port(s) to the host --volume , -v Bind mount a volume --workdir , -w Working directory inside the container
To use STREAM inside the docker container:
- Mount your data folder and enter STREAM docker container:
$ docker run --entrypoint /bin/bash -v /your/data/file/path/:/data -w /data -p 8888:8888 -it pinellolab/stream:1.0- Inside the container, launch Jupyter notebook:
root@46e09702ce87:/data# jupyter notebook --ip 0.0.0.0 --port 8888 --no-browser --allow-root
Access the notebook through your desktops browser on http://127.0.0.1:8888. The notebook will prompt you for a token which was generated when you create the notebook.
In order to make STREAM user friendly and accessible to non-bioinformatician, we have created an interactive website: http://stream.pinellolab.org
The website can also run on a local machine. More details can be found https://github.com/pinellolab/STREAM_web
Credits: H Chen, L Albergante, JY Hsu, CA Lareau, GL Bosco, J Guan, S Zhou, AN Gorban, DE Bauer, MJ Aryee, DM Langenau, A Zinovyev, JD Buenrostro, GC Yuan, L Pinello