Merge pull request #50 from saezlab/dev

Biorxiv version
saezlab · Aug 22, 2023 · 0fad24a · 0fad24a
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diff --git a/README.md b/README.md
@@ -1,4 +1,4 @@
-# LIANA+: a one-stop-shop framework for cell-cell communication <img src="https://raw.githubusercontent.com/saezlab/liana-py/dev/docs/source/_static/logo.png?raw=true" align="right" height="125">
+# LIANA+: an all-in-one framework for cell-cell communication <img src="https://raw.githubusercontent.com/saezlab/liana-py/dev/docs/source/_static/logo.png?raw=true" align="right" height="125">
 
 <!-- badges: start -->
 [![main](https://github.com/saezlab/liana-py/actions/workflows/main.yml/badge.svg)](https://github.com/saezlab/liana-py/actions)
@@ -8,19 +8,16 @@
 [![Downloads](https://pepy.tech/badge/liana)](https://pepy.tech/project/liana)
 <!-- badges: end -->
 
-LIANA+ is an efficient framework that integrates and extends existing methods and knowledge to study cell-cell communication in single-cell, spatially-resolved, and multi-modal omics data. 
+LIANA+ is an efficient framework that integrates and extends existing methods and knowledge to study cell-cell communication in single-cell, spatially-resolved, and multi-modal omics data. It works in conjunction with the [scverse ecosystem](https://github.com/scverse), and it relies on [AnnData](https://github.com/scverse/anndata) & [MuData](https://github.com/scverse/mudata) objects as input.
 
 <img src="https://raw.githubusercontent.com/saezlab/liana-py/main/docs/source/_static/abstract.png" width="700" align="center">
 
 
-## Contributions & Development
+## Development & Contributions
 
-LIANA+ is currently at it's alpha stage - i.e. we are actively working on improving it.
-
-The API visible to the user should be stable, specifically `liana.method.sc`, but some differences in terms of secondary parameters, or default settings are possible.
-
-More importantly, we welcome suggestions, ideas, and contributions! Please use do not hesitate to contact us, or use the issues or the [LIANA+ Development project](https://github.com/orgs/saezlab/projects/16) to make suggestions.
+LIANA+ is still under development. Nevertheless, the API visible to the user should be stable, specifically `liana.method.sc`.
 
+We welcome suggestions, ideas, and contributions! Please use do not hesitate to contact us, or use the issues or the [LIANA+ Development project](https://github.com/orgs/saezlab/projects/16) to make suggestions.
 
 ## Tutorials
 
@@ -30,18 +27,17 @@ More importantly, we welcome suggestions, ideas, and contributions! Please use d
 
 ### Spatial Data
 
-- [Learn spatially-informed relationships  with MISTy](https://liana-py.readthedocs.io/en/latest/notebooks/misty.html) across (multi-)views
+- [Learn spatially-informed relationships with MISTy](https://liana-py.readthedocs.io/en/latest/notebooks/misty.html) across (multi-) views.
 
-- Estimate local spatially-informed bivariate metrics with [LIANA's bivariate scores](https://liana-py.readthedocs.io/en/latest/notebooks/bivariate.html)
+- [Estimate local spatially-informed bivariate metrics](https://liana-py.readthedocs.io/en/latest/notebooks/bivariate.html). This tutorial shows how to estimate local spatially-informed bivariate metrics, such as the spatially-informed Pearson correlation coefficient or Cosine similarity.
 
 ### Multi-condition
 
-- [Hypothesis-testing for CCC with PyDeSeq2](https://liana-py.readthedocs.io/en/latest/notebooks/targeted.html) that also shows the inference of causal **intracellular** signalling networks
+- [Hypothesis-testing for CCC with PyDeSeq2](https://liana-py.readthedocs.io/en/latest/notebooks/targeted.html) that also shows the inference of causal **intracellular** signalling networks, downstream of CCC events.
 
-- [Multicellular programmes with MOFA](https://liana-py.readthedocs.io/en/latest/notebooks/mofacellular.html). Using MOFA to obtain coordinates
-gene expression programmes across samples and conditions, as done in [Ramirez et al., 2023](https://europepmc.org/article/ppr/ppr620471)
+- [Multicellular programmes with MOFA](https://liana-py.readthedocs.io/en/latest/notebooks/mofacellular.html). Using MOFA to obtain coordinates gene expression programmes across samples and conditions, as done in [Ramirez et al., 2023](https://europepmc.org/article/ppr/ppr620471).
 
-- [LIANA with MOFA](https://liana-py.readthedocs.io/en/latest/notebooks/mofatalk.html). Using MOFA to infer intercellular communication programmes across samples and conditions, as initially proposed by cell2cell-Tensor
+- [LIANA with MOFA](https://liana-py.readthedocs.io/en/latest/notebooks/mofatalk.html). Using MOFA to infer intercellular communication programmes across samples and conditions, as initially proposed by cell2cell-Tensor.
 
 - [LIANA with cell2cell-Tensor](https://liana-py.readthedocs.io/en/latest/notebooks/liana_c2c.html) to extract intercellular communication programmes across samples and conditions. Extensive tutorials combining LIANA & [cell2cell-Tensor](https://www.nature.com/articles/s41467-022-31369-2) are available [here](https://ccc-protocols.readthedocs.io/en/latest/index.html).
 
@@ -55,10 +51,9 @@ gene expression programmes across samples and conditions, as done in [Ramirez et
 For further information please check LIANA's [API documentation](https://liana-py.readthedocs.io/en/latest/api.html).
 
 
-
 ## Cite LIANA+:
 
-Dimitrov, D. ... Saez-Rodriguez, J.
+Dimitrov D., Schäfer P.S.L, Farr E., Rodriguez Mier P., Lobentanzer S., Dugourd A., Tanevski J., Ramirez Flores R.O. and Saez-Rodriguez J. 2023 LIANA+: an all-in-one cell-cell communication framework. BioRxiv. https://www.biorxiv.org/content/10.1101/2023.08.19.553863v1
 
 Dimitrov, D., Türei, D., Garrido-Rodriguez M., Burmedi P.L., Nagai, J.S., Boys, C., Flores, R.O.R., Kim, H., Szalai, B., Costa, I.G., Valdeolivas, A., Dugourd, A. and Saez-Rodriguez, J. Comparison of methods and resources for cell-cell communication inference from single-cell RNA-Seq data. Nat Commun 13, 3224 (2022). https://doi.org/10.1038/s41467-022-30755-0
 

diff --git a/docs/source/index.rst b/docs/source/index.rst
@@ -1,4 +1,4 @@
-LIANA: a one-stop-shop framework for cell-cell communication
+LIANA: an all-in-one framework for cell-cell communication
 ===========================================
 
 |MainBuild| |Issues| |Docs| |Codecov|

diff --git a/docs/source/notebooks/bivariate.ipynb b/docs/source/notebooks/bivariate.ipynb
diff --git a/docs/source/notebooks/liana_c2c.ipynb b/docs/source/notebooks/liana_c2c.ipynb
diff --git a/docs/source/notebooks/misty.ipynb b/docs/source/notebooks/misty.ipynb
diff --git a/docs/source/notebooks/mofatalk.ipynb b/docs/source/notebooks/mofatalk.ipynb
diff --git a/docs/source/reference.rst b/docs/source/reference.rst
@@ -1,7 +1,7 @@
 Reference
 ----------
 
-Dimitrov, D. ... Saez-Rodriguez, J. In prep...
+Dimitrov D., Schäfer P.S.L, Farr E., Rodriguez Mier P., Lobentanzer S., Dugourd A., Tanevski J., Ramirez Flores R.O. and Saez-Rodriguez J. 2023 LIANA+: an all-in-one cell-cell communication framework. BioRxiv. https://www.biorxiv.org/content/10.1101/2023.08.19.553863v1
 
 Dimitrov, D., Türei, D., Garrido-Rodriguez M., Burmedi P.L., Nagai, J.S., Boys, C., Flores, R.O.R., Kim, H., Szalai, B., Costa, I.G., Valdeolivas, A., Dugourd, A. and Saez-Rodriguez, J. Comparison of methods and resources for cell-cell communication inference from single-cell RNA-Seq data. Nat Commun 13, 3224 (2022). https://doi.org/10.1038/s41467-022-30755-0
 

diff --git a/docs/source/release_notes.rst b/docs/source/release_notes.rst
@@ -1,6 +1,20 @@
 Release notes
 =============
 
+1.0.0a1 (30.07.2023)
+---------------------------------------------------------
+
+- `positive_only` in bivariate metrics was renamed to `mask_negatives` will now mask only negative-negative/low-low interactions, and not negative-positive interactions.
+
+- Replaced MSigDB with transcription factor activities in MISTy's tutorial
+
+- Enable sorting according to ascending order in misty-related plots
+
+- Enable `cmap` to be passed to tileplot & dotplots
+
+- Minor Readme & tutorial improvements.
+
+
 1.0.0a0 (27.07.2023) LIANA+ Release
 ---------------------------------------------------------
 

diff --git a/liana/method/_pipe_utils/_pre.py b/liana/method/_pipe_utils/_pre.py
@@ -122,7 +122,8 @@ def prep_check_adata(adata: AnnData,
     msk_samples = adata.X.sum(axis=1).A1 == 0
     n_empty_samples = np.sum(msk_samples)
     if n_empty_samples > 0:
-        raise ValueError(f"{n_empty_samples} samples of mat are empty, please remove them.")
+        if verbose:
+            print(f"{n_empty_samples} samples of mat are empty, please remove them.")
 
     # Check if log-norm
     _sum = np.sum(adata.X.data[0:100])
@@ -133,8 +134,7 @@ def prep_check_adata(adata: AnnData,
     # Check for non-finite values
     if np.any(~np.isfinite(adata.X.data)):
         raise ValueError(
-            """mat contains non finite values (nan or inf), please set them 
-            to 0 or remove them.""")
+            "mat contains non finite values (nan or inf), please set them to 0 or remove them.")
 
     # Define idents col name
     if groupby is not None:

diff --git a/liana/method/sp/_SpatialBivariate.py b/liana/method/sp/_SpatialBivariate.py
@@ -35,7 +35,7 @@ def __call__(self,
                  connectivity_key = 'spatial_connectivities',
                  mod_added = "local_scores",
                  key_added = 'global_res',
-                 positive_only=False,
+                 mask_negatives=False,
                  add_categories = False,
                  n_perms: int = None,
                  seed = 1337,
@@ -82,8 +82,8 @@ def __call__(self,
             Key in `mdata.mod` where the local scores are stored.
         key_added: str
             Key in `mdata.uns` where the global scores are stored.
-        positive_only: bool
-            Whether to mask non-positive interactions.
+        mask_negatives: bool
+            Whether to mask negative-negative (low-low) or uncategorized interactions.
         add_categories: bool
             Whether to add categories about the local scores
         n_perms: int
@@ -223,17 +223,17 @@ def __call__(self,
         # reorder columns, NOTE: why?
         xy_stats = xy_stats.reindex(columns=sorted(xy_stats.columns))
 
-        if add_categories or positive_only:
+        if add_categories or mask_negatives:
             local_cats = _categorize(x_mat=x_mat,
                                      y_mat=y_mat,
                                      weight=weight,
                                      idx=mdata.obs.index,
                                      columns=xy_stats['interaction'],
                                      )
-            pos_msk = local_cats > 0
+            local_msk = local_cats != 0
         else:
             local_cats = None
-            pos_msk = None
+            local_msk = None
 
         # get local scores
         xy_stats, local_scores, local_pvals = \
@@ -245,15 +245,15 @@ def __call__(self,
                                  weight=weight,
                                  seed=seed,
                                  n_perms=n_perms,
-                                 positive_only=positive_only,
-                                 pos_msk=pos_msk,
+                                 mask_negatives=mask_negatives,
+                                 local_msk=local_msk,
                                  verbose=verbose,
                                  )
         local_scores = obsm_to_adata(adata=mdata, df=local_scores, obsm_key=None, _uns=mdata.uns)
         local_scores.uns[key_added] = xy_stats
 
-        if positive_only:
-            local_scores.X = local_scores.X * pos_msk.T
+        if mask_negatives:
+            local_scores.X = local_scores.X * local_msk.T
         if local_cats is not None:
             local_scores.layers['cats'] = csr_matrix(local_cats.T)
         if local_pvals is not None:

diff --git a/liana/method/sp/_lr_bivar.py b/liana/method/sp/_lr_bivar.py
@@ -20,7 +20,7 @@ def __call__(self,
                  interactions=None,
                  expr_prop: float = 0.05,
                  n_perms: int = None,
-                 positive_only: bool = False,
+                 mask_negatives: bool = False,
                  seed: int = 1337,
                  add_categories: bool = False,
                  use_raw: Optional[bool] = True,
@@ -92,7 +92,7 @@ def __call__(self,
             interactions=interactions,
             nz_threshold=expr_prop,
             n_perms=n_perms,
-            positive_only=positive_only,
+            mask_negatives=mask_negatives,
             add_categories=add_categories,
             x_mod=True,
             y_mod=True,