Web application for exploration of large scale scRNA-seq datasets, upgraded to enable end-to-end interactive analysis.
Reason this release was yanked:
Bug with scatter plots
Project description
Exploratory CellxGene (ExCellxGene)
This fork implements some of the key features that have been highly requested by the data science team at CZBiohub.
Features include:
- Hotkeys (SHIFT+? to see a tooltip describing all available hotkeys)
- End-to-end interactive analysis and reembedding, with new embeddings hierarchically organized.
- LIDAR graph interaction mode (the airplane) - Show an interactive tooltip describing the cells underneath your cursor. Very helpful for the color impaired or for large datasets with hundreds of labels.
- Sankey plots
- Leiden clustering
- Label fusion and deletion
- Interactive selection of data layer for expression visualization
- Many other quality-of-life improvements.
Patch notes (v1.2.5)
- When displaying continuous metadata, cells with value zero are drawn as if they are unselected to send them to the background.
- Category and geneset menus now have a new menu item to include/exclude zeros from the histograms. This is useful when the distributions are super zero-inflated.
Patch notes (v1.2.3)
- Gene sets are now grouped based on their descriptions under collapsible headers.
- Gene sets are now more compact, displaying 10 genes at a time with buttons to flip through pages.
- Differential expression now calculates the top 100 genes.
- A new button in the menubar allows you to calculate marker genes for all labels in a selected category.
- Embeddings are now indented according to their hierarchical organization, and nested embeddings are collapsible.
- Categorical labels are now sortable based on the currently displayed continuous medatada.
- All preprocessing and reembedding parameters now have a tooltip.
- Added a button to display hotkey menu to the menubar.
- Various bugfixes.
Installation
- Install miniconda if conda not available already:
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh -O ~/miniconda.sh
bash ~/miniconda.sh -b -p $HOME/miniconda
- Create and activate a new environment (we need to install the TBB threading layer as well):
conda create -n cxg python=3.8
conda activate cxg
conda install tbb=2020.3 tbb-devel=2020.3
- Install excellxgene with pip:
pip install excellxgene
If your operating system is CentOS, then you may run into issues installing dependencies that require up-to-date gcc or g++ compilers. Please install with the following and try reinstalling excellxgene with pip:
conda install -c conda-forge gcc cxx-compiler
- Download the git repository to get the example datasets (assumes git is available, if not install it with conda install -c anaconda git)
git clone https://github.com/czbiohub/excellxgene
cd excellxgene
Datasets are stored in example-dataset
- Launch excellxgene with:
excellxgene launch example-dataset
This should launch an excellxgene session with all the datasets in example-datasets/ loaded in.
If you're running excellxgene remotely, please launch with:
excellxgene launch example-datasets --host 0.0.0.0
Ping me on the Biohub slack (@Alec) if you have any questions!
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
File details
Details for the file excellxgene-2.3.4.tar.gz.
File metadata
- Download URL: excellxgene-2.3.4.tar.gz
- Upload date:
- Size: 6.9 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.7.1 importlib_metadata/4.10.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 5d42d1586332b999d70d57c52222fdf6d285ada31b9985654ec086716f5815a0 |
|
| MD5 | da9438ed5f94340a58fa51708605dcc4 |
|
| BLAKE2b-256 | 40d31f9fb371bdc6472f53b32131850400bc05bd4b7024b30e96dc519a972c3b |
