Merge pull request #228 from saezlab/metalinks_access

Metalinks access

Author: dbdimitrov

.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 1.7.0
+current_version = 1.7.1
 commit = True
 tag = True
 

CHANGELOG.md

@@ -1,5 +1,11 @@
 # Changelog
 
+## 1.7.1 (24.01.2026)
+
+- Fixed issue with Metalinks download due to User-Agent restrictions.
+- Added scanpy version compatibility using getattr to handle both _set_default_colors_for_categorical_obs (old) and set_default_colors_for_categorical_obs (new).
+
+
 ## 1.7.0 (07.01.2026)
 
 - Inflow implementation and tutorial #221 by @AtheerAS

README.md

@@ -20,29 +20,51 @@ We welcome suggestions, ideas, and contributions! Please do not hesitate to cont
 A set of extensive vignettes can be found in the [LIANA+ documentation](https://liana-py.readthedocs.io/en/latest/).
 
 ## Decision Tree
-### Does the data contain spatial coordinates?
-#### Yes
-- **Q: Bivariate or unsupervised, multi-variate, and multi-view analysis?**
-  - **Bivariate:**
-    - **Q: Are you interested in identifying the subregions of interactions (i.e., local interactions)?**
-      - **Yes:** Check the [**Local** Bivariate Metrics](https://liana-py.readthedocs.io/en/latest/notebooks/bivariate.html#Bivariate-Ligand-Receptor-Relationships)
-      - **No:** Check the [**Global** Bivariate Metrics](https://liana-py.readthedocs.io/en/latest/notebooks/bivariate.html#Bivariate-Ligand-Receptor-Relationships)
-  - **Unsupervised:** [Multi-view learning](https://liana-py.readthedocs.io/en/latest/notebooks/misty.html)
-
-#### No
-- **Q: Are you interested in comparing CCC across samples?**
-  - **Yes:**
-    - **Q: Are you interested in a specific contrast?**
-      - **Yes:** [Differential Contrasts and Downstream Signalling](https://liana-py.readthedocs.io/en/latest/notebooks/targeted.html)
-      - **No:** Unsupervised Cross-conditional LR inference with [MOFA+](https://liana-py.readthedocs.io/en/latest/notebooks/mofatalk.html) or [Tensor-cell2cell](https://liana-py.readthedocs.io/en/latest/notebooks/liana_c2c.html)
-  - **No:** [Steady-state Ligand-Receptor inference](https://liana-py.readthedocs.io/en/latest/notebooks/basic_usage.html)
-
-### Is your data Multi-modal?
-- **Spatial:** [Integrating Multi-Modal Spatially-Resolved Technologies](https://liana-py.readthedocs.io/en/latest/notebooks/sma.html)
-- **Non-Spatial:** [Integrating Multi-Modal Single-Cell Technologies](https://liana-py.readthedocs.io/en/latest/notebooks/sc_multi.html)
-
-#### Infer Metabolite-mediated CCC from transcriptomics?
-- [Non-spatial Data](https://liana-py.readthedocs.io/en/latest/notebooks/sc_multi.html#Metabolite-mediated-CCC-from-Transcriptomics-Data)
+
+```mermaid
+flowchart TD
+    Start[What type of data?] --> Spatial{Spatial<br/>coordinates?}
+    Start --> Modal{Multi-modal?}
+
+    %% Spatial branch
+    Spatial -->|Yes| SpatialRes{Resolution?}
+    SpatialRes -->|Single-cell| Inflow[Inflow Score]
+    SpatialRes -->|Spot-based| SpatialType{Analysis type?}
+    SpatialType -->|Bivariate| LocalQ{Local<br/>interactions?}
+    LocalQ -->|Yes| Local[Local Bivariate Metrics]
+    LocalQ -->|No| Global[Global Bivariate Metrics]
+    SpatialType -->|Unsupervised| MISTy[Multi-view Learning]
+
+    %% Non-spatial branch
+    Spatial -->|No| Compare{Compare across<br/>samples?}
+    Compare -->|Yes| Contrast{Specific<br/>contrast?}
+    Contrast -->|Yes| Targeted[Differential Contrasts]
+    Contrast -->|No| MOFA[MOFA+]
+    Contrast -->|No| Tensor[Tensor-cell2cell]
+    Tensor --> TensorExt[Extended Tutorials]
+    Compare -->|No| Steady[Steady-state LR Inference]
+
+    %% Multi-modal branch
+    Modal -->|Spatial| SMA[Multi-Modal Spatial]
+    Modal -->|Non-Spatial| SCMulti[Multi-Modal Single-Cell]
+
+    %% Metabolite sub-branch
+    SCMulti --> Metab[Metabolite-mediated CCC]
+
+    %% Links (click events)
+    click Inflow "https://liana-py.readthedocs.io/en/latest/notebooks/inflow_score.html"
+    click Local "https://liana-py.readthedocs.io/en/latest/notebooks/bivariate.html"
+    click Global "https://liana-py.readthedocs.io/en/latest/notebooks/bivariate.html"
+    click MISTy "https://liana-py.readthedocs.io/en/latest/notebooks/misty.html"
+    click Targeted "https://liana-py.readthedocs.io/en/latest/notebooks/targeted.html"
+    click MOFA "https://liana-py.readthedocs.io/en/latest/notebooks/mofatalk.html"
+    click Tensor "https://liana-py.readthedocs.io/en/latest/notebooks/liana_c2c.html"
+    click TensorExt "https://ccc-protocols.readthedocs.io/en/latest/"
+    click Steady "https://liana-py.readthedocs.io/en/latest/notebooks/basic_usage.html"
+    click SMA "https://liana-py.readthedocs.io/en/latest/notebooks/sma.html"
+    click SCMulti "https://liana-py.readthedocs.io/en/latest/notebooks/sc_multi.html"
+    click Metab "https://liana-py.readthedocs.io/en/latest/notebooks/sc_multi.html#Metabolite-mediated-CCC"
+```
 
 ## API
 For further information please check LIANA's [API documentation](https://liana-py.readthedocs.io/en/latest/api.html).

pyproject.toml

@@ -4,7 +4,7 @@ requires = [ "hatchling" ]
 
 [project]
 name = "liana"
-version = "1.7.0"
+version = "1.7.1"
 description = "LIANA+: a one-stop-shop framework for cell-cell communication"
 readme = "README.md"
 license = { file = "LICENSE" }

src/liana/__init__.py

@@ -1,4 +1,4 @@
-__version__ = '1.7.0'
+__version__ = '1.7.1'
 
 from liana import method as mt, plotting as pl, resource as rs, multi as mu, utils as ut, testing
 

src/liana/plotting/_circle_plot.py

@@ -54,7 +54,13 @@ def _set_adata_color(adata, label, color_dict=None, hex=True):
         ]
     else:
         if f"{label}_colors" not in adata.uns:
-            sc.pl._utils._set_default_colors_for_categorical_obs(adata, label)
+            # Handle both old (_set_default...) and new (set_default...) scanpy API
+            _set_colors = getattr(
+                sc.pl._utils,
+                '_set_default_colors_for_categorical_obs',
+                getattr(sc.pl._utils, 'set_default_colors_for_categorical_obs', None)
+            )
+            _set_colors(adata, label)
 
     return adata
 

src/liana/resource/get_metalinks.py

@@ -19,30 +19,23 @@ def _download_metalinksdb(verbose=True):
     """
     requests = _check_if_installed("requests")
 
-    METALINKS_URL = "https://figshare.com/ndownloader/files/60861292"
+    # GitHub Releases URL (CI-friendly, no WAF issues)
+    METALINKS_URL = "https://github.com/saezlab/liana-py/releases/download/metalinksdb/metalinksdb.db"
 
-    # Define the local filename to save the downloaded database
     db_file_name = 'metalinksdb.db'
     db_path = os.path.join(os.getcwd(), db_file_name)
 
-    # Check if the database file already exists and is valid
     if os.path.exists(db_path):
-        # Check if file is empty or corrupted
         if os.path.getsize(db_path) == 0:
             _logg("Existing database file is empty. Removing and re-downloading...", verbose=verbose)
             os.remove(db_path)
         else:
             return db_path
 
-    # Download the database
     _logg("Downloading database...", verbose=verbose)
     try:
-        # Figshare requires a browser-like User-Agent to bypass WAF
-        headers = {
-            'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36'
-        }
-        response = requests.get(METALINKS_URL, headers=headers, stream=True, allow_redirects=True)
-        response.raise_for_status()  # Raise an error for bad status codes
+        response = requests.get(METALINKS_URL, stream=True, allow_redirects=True)
+        response.raise_for_status()
 
         with open(db_path, 'wb') as f:
             for chunk in response.iter_content(chunk_size=8192):

tests/test_converters.py

@@ -27,7 +27,7 @@ def zi_minmax_cutoff(x):
     adata = mdata_to_anndata(mdata, x_mod='adata_x', y_mod='adata_y',
                              x_transform=zi_minmax_cutoff, y_transform=zi_minmax_cutoff,
                              verbose=False)
-    assert_almost_equal(adata.X.sum(), 2120.704, decimal=4)
+    assert_almost_equal(adata.X.sum(), 2120.704, decimal=3)
 
     # test non-negative
     from scanpy.pp import scale

tests/test_spatial_utils.py

@@ -11,37 +11,37 @@
 def test_get_spatial_connectivities():
     spatial_neighbors(adata=adata, bandwidth=200, set_diag=True, cutoff=0.2)
     np.testing.assert_equal(adata.obsp['spatial_connectivities'].shape, (adata.shape[0], adata.shape[0]))
-    np.testing.assert_equal(adata.obsp['spatial_connectivities'].sum(), 4550.654013895928)
+    np.testing.assert_almost_equal(adata.obsp['spatial_connectivities'].sum(), 4550.654013895928, decimal=4)
 
     spatial_neighbors(adata=adata, bandwidth=100, set_diag=True, cutoff=0.1)
-    np.testing.assert_equal(adata.obsp['spatial_connectivities'].sum(), 1802.332962418902)
+    np.testing.assert_almost_equal(adata.obsp['spatial_connectivities'].sum(), 1802.332962418902, decimal=4)
 
     conns = spatial_neighbors(adata=adata, bandwidth=100,
                               kernel='linear', cutoff=0.1,
                               set_diag=True, inplace=False)
-    assert conns.sum() == 899.065036633088
+    np.testing.assert_almost_equal(conns.sum(), 899.065036633088, decimal=4)
 
     conns = spatial_neighbors(adata=adata, bandwidth=100,
                               kernel='exponential', cutoff=0.1,
                               set_diag=True, inplace=False)
-    assert conns.sum() == 1520.8496098963612
+    np.testing.assert_almost_equal(conns.sum(), 1520.8496098963612, decimal=4)
 
     conns = spatial_neighbors(adata=adata, bandwidth=100, set_diag=True,
                               kernel='misty_rbf', cutoff=0.1,
                               inplace=False)
-    assert conns.sum() == 1254.3161716188595
+    np.testing.assert_almost_equal(conns.sum(), 1254.3161716188595, decimal=4)
 
     conns = spatial_neighbors(adata=adata, bandwidth=250, set_diag=False,
                               max_neighbours=100,
                               kernel='gaussian', cutoff=0.1,
                               inplace=False)
-    assert conns.sum() == 6597.05237692107
+    np.testing.assert_almost_equal(conns.sum(), 6597.05237692107, decimal=4)
 
     conns = spatial_neighbors(adata=adata, bandwidth=250,
                               set_diag=False, max_neighbours=100,
                               kernel='gaussian', cutoff=0.1,
                               inplace=False, standardize=True)
-    np.testing.assert_almost_equal(conns.sum(), conns.shape[0])
+    np.testing.assert_almost_equal(conns.sum(), conns.shape[0], decimal=4)
 
 # toy test data
 seed = 0