Merge pull request #543 from theislab/release

Release 3.10

.bandit.yml

@@ -4,4 +4,4 @@
 tests: []
 
 # (optional) list skipped tests here:
-skips: ['B101', 'B403', 'B404', 'B603', 'B607', 'B301', 'B303', 'B311', 'B310', 'B506', 'B321', 'B402']
+skips: ['B101', 'B403', 'B404', 'B603', 'B607', 'B301', 'B303', 'B311', 'B310', 'B506', 'B321', 'B402', 'B105', 'B602']

.github/ISSUE_TEMPLATE/data_loader.md

@@ -0,0 +1,41 @@
+---
+name: Data loader request
+about: Suggest a new dataset to add to sfaira.
+title: 'Dataset summary'
+labels: 'dataset'
+assignees: ''
+
+---
+
+**Is your dataset not yet in sfaira?**
+Please search the sfaira [code](https://github.com/theislab/sfaira/tree/dev), and [issues and PRs](https://github.com/theislab/sfaira/issues?q=) for any DOI associated with this dataset, such as preprints or journal publications. To be safe, you can also search for the first author.
+
+**Describe the data set**
+Fill in below:
+
+- Link to publication:
+- Title of publication:
+- First author of publication:
+- DOI preprint:
+- DOI journal:
+- Download link to any data objects required:
+
+**Describe meta data**
+Optionally, you can already collect meta data information here before starting to write the data loader, or to help others write one.
+You can extend these lists if you find more meta data that you want to record before writing a data loader.
+Note that you can also directly put this information into a draft data loader and start a pull request instead of first writing an issue.
+If you know this dataset well but cannot write a loader right now, this will help other people decide if they want to write a loader for this dataset and will speed up their process.
+
+- Is this primary data (not a meta study):
+- Is most raw gene expression matrix normalized (if yes how)?:
+- Single-cell assay used:
+- Disease(s) of sampled individuals (ideally MONDO term):
+- Organ(s) sampled (ideally UBERON term):
+- Organism(s) sampled (ideally NCBItaxon term):
+
+Any relevant cell-wise annotation fields that are column names of a table or column names in `.obs` of an `h5ad` for example:
+
+- Cell type annotation:
+
+**Additional context**
+Add any other context of the dataset or anticipated issues with the dataloader.

.github/workflows/build_package.yml

@@ -22,8 +22,8 @@ jobs:
         with:
           python-version: ${{ matrix.python }}
 
-      - name: Upgrade and install pip
-        run: python -m pip install --upgrade pip
+      - name: Upgrade and install pip and wheel
+        run: python -m pip install --upgrade pip wheel
 
       - name: Build sfaira
         run: pip install .

.github/workflows/create_templates.yml

@@ -21,13 +21,15 @@ jobs:
         with:
           python-version: 3.8
 
-      - name: Upgrade and install pip
-        run: python -m pip install --upgrade pip
+      - name: Upgrade and install pip and wheel
+        run: python -m pip install --upgrade pip wheel
 
       - name: Build sfaira
         run: pip install .
 
       - name: Create single_dataset template
         run: |
-          echo -e "\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n" | sfaira create-dataloader
-          rm -rf d10_1000_j_journal_2021_01_001/
+          mkdir -p ./d10_1000_j_journal_2022_01_001
+          echo -e "\nEinstein, Albert\n\n10.1000/j.journal.2022.01.001\n1\nX_umap\nURL\nURL2\nHomo sapiens\nY2022\nX\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nindex\n\n" | sfaira create-dataloader
+          sfaira validate-dataloader --doi 10.1000/j.journal.2022.01.001
+          rm -rf ./d10_1000_j_journal_2022_01_001

.github/workflows/publish_docs.yml

@@ -23,8 +23,8 @@ jobs:
         with:
           python-version: 3.8
 
-      - name: Install pip
-        run: python -m pip install --upgrade pip
+      - name: Upgrade and install pip and wheel
+        run: python -m pip install --upgrade pip wheel
 
       - name: Install doc dependencies
         run: pip install -r docs/requirements.txt

README.rst

@@ -25,22 +25,19 @@
 sfaira - data and model repository for single-cell data
 =======================================================
 
-.. image:: https://github.com/theislab/sfaira/blob/main/resources/images/concept.png
+.. image:: https://github.com/theislab/sfaira/blob/release/resources/images/figure_rtd_intro.png
    :width: 400px
    :align: center
 
 sfaira_ is a model and a data repository in a single python package (`full paper`_).
 We provide an interactive overview of the current state of the zoos on sfaira-portal_.
 
 Its data zoo gives users access to streamlined data loaders that allow reproducible use of published and private data sets for model training and exploration.
-Its model zoo gives user streamlined access to pre-trained models and to common model architectures to ease usage of neural networks in common single-cell analysis workflows:
-A model zoo is a software infrastructure that improves user access to pre-trained models which are separately published, such as DCA_ or scArches_:
+Its model zoo gives user streamlined access to pre-trained models and to common model architectures to ease usage of neural networks in common single-cell analysis workflows.
 Instead of focussing on developing new models, we focus on making models easily accessible to users and distributable by developers.
 sfaira integrates into scanpy_ workflows.
 
 .. _scanpy: https://github.com/theislab/scanpy
 .. _sfaira: https://sfaira.readthedocs.io
 .. _full paper: https://genomebiology.biomedcentral.com/articles/10.1186/s13059-021-02452-6
-.. _DCA: https://github.com/theislab/dca
-.. _scArches: https://github.com/theislab/scarches
 .. _sfaira-portal: https://theislab.github.io/sfaira-portal/