CostaLab · jsnagai · Jun 22, 2026 · Oct 17, 2025 · Oct 17, 2025 · Feb 2, 2026
diff --git a/.github/workflows/pipypublish.yaml b/.github/workflows/pipypublish.yaml
@@ -0,0 +1,33 @@
+name: Publish to PyPI
+
+on:
+  release:
+    types: [ published ]
+    branches: [ main ]
+  workflow_dispatch:
+
+jobs:
+  build-and-publish:
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout sources
+        uses: actions/checkout@v2
+
+      - name: Setup Python
+        uses: actions/setup-python@v2
+        with:
+          python-version: "3.11"
+
+      - name: Install poetry and dependencies
+        run: |
+          python -m pip install --upgrade pip
+          python -m pip install poetry
+
+      - name: Configure poetry
+        env:
+          pypi_token: ${{ secrets.PYPI }}
+        run: poetry config pypi-token.pypi $pypi_token
+
+      - name: Build and publish
+        run: yes | poetry publish --build
diff --git a/.python-version b/.python-version
@@ -0,0 +1 @@
+3.11
diff --git a/CHANGELOG.rst b/CHANGELOG.rst
@@ -0,0 +1,17 @@
+
+2026-02-10
+==========
+
+ Removed
+ -------
+
+ - Refactor in generate_report
+
+Added
+-----
+
+ - Add save option in generate_report
+ - fix fisher_test
+
+2026-02-10
+==========
diff --git a/README.md b/README.md
@@ -2,6 +2,13 @@
 
 <img src="https://github.com/CostaLab/pyCrossTalkeR/blob/main/logo1.png" align="right" width="200" />
 
+
+<!-- Python versions supported -->
+[![Python Versions](https://img.shields.io/pypi/pyversions/pycrosstalker?cacheSeconds=300)](https://pypi.org/project/pycrosstalker/)
+[![Downloads](https://img.shields.io/pypi/dm/pycrosstalker?cacheSeconds=300)](https://pypi.org/project/pycrosstalker/)
+[![License](https://img.shields.io/pypi/l/pycrosstalker?cacheSeconds=300)](https://pypi.org/project/pycrosstalker/)
+[![PyPI version](https://img.shields.io/pypi/v/pycrosstalker?cacheSeconds=300)](https://pypi.org/project/pycrosstalker/)
+
 James S. Nagai<sup>1</sup>,
 Vanessa Kloeker<sup>1</sup>,
 Ruthvik Koppala<sup>1</sup>,
@@ -24,6 +31,7 @@ Ivan G. Costa<sup>1*</sup>
 
 ![Alt text](image.png)
 
+
 **Motivation:** Ligand-receptor (LR) analysis allows the characterization of cellular crosstalk from single cell RNA-seq data. However, current LR methods provide limited approaches for prioritization of cell types, ligands or receptors or characterizing changes in crosstalk between two biological conditions.
 
 **Results:** pyCrossTalkeR is a framework for network analysis and visualisation of LR networks. pyCrossTalkeR identifies relevant ligands, receptors and cell types contributing to changes in cell communication when contrasting two biological states: disease vs. homeostasis. A case study on scRNA-seq of human myeloproliferative neoplasms reinforces the strengths of pyCrossTalkeR for characterisation of changes in cellular crosstalk in disease state.
@@ -51,7 +59,7 @@ libgeos-dev
 ```
 
 
-## Features v2.0.0
+## Features v2.1.3
 
 
 - Single and Comparative Reports
@@ -61,6 +69,7 @@ libgeos-dev
       - All measures and PC table
       - PC1 and PC2 based barplot
    - LR pair visualization plot can be done
+   - Statistical tests for both interaction amount and also interaction strenght
 
 
 # References

diff --git a/dist/pycrosstalker-2.1.0-py3-none-any.whl b/dist/pycrosstalker-2.1.0-py3-none-any.whl
diff --git a/dist/pycrosstalker-2.1.0.tar.gz b/dist/pycrosstalker-2.1.0.tar.gz
diff --git a/dist/pycrosstalker-2.1.3-py3-none-any.whl b/dist/pycrosstalker-2.1.3-py3-none-any.whl
diff --git a/dist/pycrosstalker-2.1.3.tar.gz b/dist/pycrosstalker-2.1.3.tar.gz
diff --git a/dist/pycrosstalker-2.1.4-py3-none-any.whl b/dist/pycrosstalker-2.1.4-py3-none-any.whl
diff --git a/dist/pycrosstalker-2.1.4.tar.gz b/dist/pycrosstalker-2.1.4.tar.gz
diff --git a/dist/pycrosstalker-2.1.5rc0-py3-none-any.whl b/dist/pycrosstalker-2.1.5rc0-py3-none-any.whl
diff --git a/dist/pycrosstalker-2.1.5rc0.tar.gz b/dist/pycrosstalker-2.1.5rc0.tar.gz
diff --git a/dist/pycrosstalker-2.1.6-py3-none-any.whl b/dist/pycrosstalker-2.1.6-py3-none-any.whl
diff --git a/dist/pycrosstalker-2.1.6.tar.gz b/dist/pycrosstalker-2.1.6.tar.gz
diff --git a/docs/source/Human_Myelofibrosis.md b/docs/source/Human_Myelofibrosis.md
@@ -2,7 +2,7 @@
 
 ```{toctree}
 ---
-maxdepth: 3
+maxdepth: 2
 ---
 notebooks/Human_Myelofibrosis.ipynb
 ```
diff --git a/docs/source/Human_Myocardial_Infarction.md b/docs/source/Human_Myocardial_Infarction.md
@@ -2,7 +2,7 @@
 
 ```{toctree}
 ---
-maxdepth: 3
+maxdepth: 2
 ---
 notebooks/Human_Myocardial_Infarction.ipynb
 ```
diff --git a/docs/source/api.md b/docs/source/api.md
@@ -15,10 +15,8 @@ Import pycrosstalker as:
 import pycrosstalker
 ```
 
-
 ```{toctree}
-:maxdepth: 2
-
-tools
-plots
+   :maxdepth: 1
+   tools
+   plots
 ```
diff --git a/docs/source/conf.py b/docs/source/conf.py
@@ -7,12 +7,15 @@
 # -- Project information -----------------------------------------------------
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information
 
+
 project = 'pyCrossTalkeR'
-copyright = '2025, Ruthvik Koppala'
-author = 'Ruthvik Koppala'
+copyright = '2025, James Nagai'
+author = 'James Nagai'
 
 # -- General configuration ---------------------------------------------------
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration
+
+
 version = '0.1.8.8'
 
 extensions = [

diff --git a/docs/source/index.md b/docs/source/index.md
@@ -34,7 +34,6 @@ You can install pyCrossTalkeR with the simple commands below:
 
 ```
 pip install pycrosstallker
-
 ```
 
 

diff --git a/docs/source/notebooks/.ipynb_checkpoints/Human_Myocardial_Infarction-checkpoint.ipynb b/docs/source/notebooks/.ipynb_checkpoints/Human_Myocardial_Infarction-checkpoint.ipynb
diff --git a/docs/source/notebooks/.ipynb_checkpoints/pyCrossTalkeR-checkpoint.ipynb b/docs/source/notebooks/.ipynb_checkpoints/pyCrossTalkeR-checkpoint.ipynb
diff --git a/docs/source/notebooks/Human_Myelofibrosis.ipynb b/docs/source/notebooks/Human_Myelofibrosis.ipynb
diff --git a/docs/source/notebooks/Human_Myocardial_Infarction.ipynb b/docs/source/notebooks/Human_Myocardial_Infarction.ipynb
diff --git a/poetry.lock b/poetry.lock
diff --git a/pycrosstalker/__init__.py b/pycrosstalker/__init__.py
@@ -1,9 +1,7 @@
-__version__ = "1.0.1"
-__author__ = 'Ruthvik Koppala'
+__version__ = "2.1.6"
+__author__ = 'James Nagai'
 __credits__ = 'Institute for Computational Genomics'
 
 import pycrosstalker.tools as tl
 import pycrosstalker.plots as pl
 
-
-#Atfan helped to translate some of the code
diff --git a/pycrosstalker/__pycache__/__init__.cpython-311.pyc b/pycrosstalker/__pycache__/__init__.cpython-311.pyc
diff --git a/pycrosstalker/__pycache__/__init__.cpython-312.pyc b/pycrosstalker/__pycache__/__init__.cpython-312.pyc
diff --git a/pycrosstalker/plots/__pycache__/__init__.cpython-311.pyc b/pycrosstalker/plots/__pycache__/__init__.cpython-311.pyc
diff --git a/pycrosstalker/plots/__pycache__/__init__.cpython-312.pyc b/pycrosstalker/plots/__pycache__/__init__.cpython-312.pyc
diff --git a/pycrosstalker/plots/__pycache__/plot.cpython-311.pyc b/pycrosstalker/plots/__pycache__/plot.cpython-311.pyc
diff --git a/pycrosstalker/plots/__pycache__/plot.cpython-312.pyc b/pycrosstalker/plots/__pycache__/plot.cpython-312.pyc
diff --git a/pycrosstalker/plots/plot.py b/pycrosstalker/plots/plot.py
@@ -5,16 +5,13 @@
 import matplotlib.cm as cm
 import matplotlib.colors as mcolors
 import seaborn as sns
-import plotly.colors as pc
 import plotly.graph_objects as go
-from plotnine import *
 from adjustText import adjust_text
 from gprofiler import GProfiler
 from sankeyflow import Sankey
-import json
 
 
-def plot_cci(graph, colors, plt_name, coords, pg, emax=None, leg=False, low=25, high=75, ignore_alpha=False, log=False, efactor=8, vfactor=12, vnames=True, figsize=None, scale_factor=2, node_size=2, font_size=10):
+def plot_cci(graph, colors, plt_name, coords, pg, emax=None, leg=False, low=25, high=75, ignore_alpha=False, log=False, efactor=8, vfactor=12, vnames=True, figsize=None, scale_factor=2, node_size=2, font_size=10,return_figure=False):
     """
     This function does a CCI plot
 
@@ -37,17 +34,21 @@ def plot_cci(graph, colors, plt_name, coords, pg, emax=None, leg=False, low=25,
     high :
         Higher threshould which will be filtered. Edges within the interval [low\,high] are filtered.
     ignore_alpha :
-        not include transparency on the plot
+        Not include transparency on the plot edges
     log :
-        logscale the interactions
+        Logscale the interactions
     efactor :
-        edge scale factor
+        Edge scale factor
     vfactor :
-        edge scale factor
+        Certex scale factor
     vnames :
-        remove vertex labels
+        Remove vertex labels
     pg :
-        pagerank values
+        Pagerank values
+    figsize:
+        Set matplotlib figsize
+    return_figure:
+        Option for return matplotlib figure axes
 
     Returns
     -------
@@ -127,21 +128,21 @@ def plot_cci(graph, colors, plt_name, coords, pg, emax=None, leg=False, low=25,
         min_pg, max_pg = min(pg), max(pg)
         legend1 = ax.legend(loc='lower left', title="Pagerank",
                 handles=[plt.Line2D([], [], linestyle='', marker='o', markersize=v / vfactor, markerfacecolor='black', markeredgecolor='none') for v in [min_pg, (min_pg + max_pg) / 2, max_pg]],
-                labels=[round(min_pg, 2), round((min_pg + max_pg) / 2, 2), round(max_pg, 2)],  bbox_to_anchor=(0.8, 0))
+                labels=[round(min_pg, 2), round((min_pg + max_pg) / 2, 2), round(max_pg, 2)], bbox_to_anchor=(0.95, 0.3))
 
     # Thickness legend
     non_zero_inter_edges = [d['inter'] for _, _, d in graph.edges(data=True) if d.get('inter', 0) != 0]
     if non_zero_inter_edges:
         e_wid_sp = [round(min(non_zero_inter_edges), 2), round(min(non_zero_inter_edges) + (emax / 2), 2), round(emax, 2)]
-        legend2 = ax.legend(e_wid_sp, title='Percentage of \nthe interactions', title_fontsize='small', loc='upper left', bbox_to_anchor=(0.8, 0.4))
+        legend2 = ax.legend(e_wid_sp, title='Percentage of \nthe interactions', title_fontsize='small', loc='upper left', bbox_to_anchor=(0.95, 0.7))
 
     ax.add_artist(legend1)
-    ax.add_artist(legend2)
-
     ax.set_title(plt_name)
     # Show the plot
     plt.tight_layout()
     plt.show()
+    if return_figure:
+        return (fig,ax)
 
 
 def plot_pca_LR_comparative(lrobj_tblPCA, pca_table, dims=(1, 2), ret=False, ggi=True, include_tf=False, gene_types="all"):
@@ -768,7 +769,7 @@ def plot_volcane(df, method, p_threshold=0.05, fc_threshold=1, figsize=(8, 6), a
     plt.show()
 
 
-def plot_clustermap(data, title, annot=True):
+def plot_clustermap(data, title, annot=True, return_figure=False):
     """
     This function generates a Clustermap plot
 
@@ -780,15 +781,16 @@ def plot_clustermap(data, title, annot=True):
         Title of the plot
     annot : bool
         Whether to annotate the heatmap with values
-
+    return_figure:
+        Option for return matplotlib figure axes
     Returns
     -------
+
     Python Cluster map
 
     """
     pivot_table = data.groupby(["source", "target"])["LRScore"].sum().unstack().fillna(0)
-    xlabel, ylabel = "Target Tissue", "Source Tissue"
-
+    xlabel, ylabel = "Target", "Source"
     g = sns.clustermap(
         pivot_table,
         figsize=(9, 7),
@@ -799,13 +801,12 @@ def plot_clustermap(data, title, annot=True):
         dendrogram_ratio=(0.2, 0.2),
         cbar_pos=(0.02, 0.8, 0.03, 0.15)
     )
-
     g.ax_heatmap.set_xlabel(xlabel)
     g.ax_heatmap.set_ylabel(ylabel)
     plt.title(title, fontsize=14)
-
     plt.show()
 
+
 def plot_graph_clustermap(graph, weight="LRScore", title="Ligand-Receptor Heatmap", annot=True):
     """
     This function generates the graph adjacency matrix Heatmap

diff --git a/pycrosstalker/tools/Single_Condition.py b/pycrosstalker/tools/Single_Condition.py
@@ -9,7 +9,8 @@
 
 def read_lr_single_condition(input, sel_columns, out_path="/tmp/", sep=",", colors=None):
     """
-    This function loads the single conditions LR outputs and use it to generate the report data and it`s object It assumes that the table presents the following columns Ligand, Ligand.Cluster, Receptor,Receptor.Cluster and MeanLR/another measure
+    This function loads the single conditions LR outputs and use it to generate the report data and it`s object. 
+    It assumes that the table presents the following columns Ligand, Ligand.Cluster, Receptor,Receptor.Cluster and MeanLR/another measure
 
     Parameters
     ----------
@@ -114,7 +115,7 @@ def read_lr_single_condition(input, sel_columns, out_path="/tmp/", sep=",", colo
     coords = {node: c[i] for i, node in enumerate(sorted(set(unif_celltypes), key=lambda x: x.lower()), start=0)}
 
     if colors is None:
-        matplot_colors = plt.cm.get_cmap('Paired', len(set(unif_celltypes)))
+        matplot_colors = plt.get_cmap('Paired', len(set(unif_celltypes)))
         colors = {node: mcolors.to_hex(matplot_colors(i)) for i, node in enumerate(sorted(set(unif_celltypes), key=lambda x: x.lower()), start=0)}
 
     lr = {"graphs": graphs,

diff --git a/pycrosstalker/tools/__pycache__/Comparative_condition.cpython-311.pyc b/pycrosstalker/tools/__pycache__/Comparative_condition.cpython-311.pyc
diff --git a/pycrosstalker/tools/__pycache__/Comparative_condition.cpython-312.pyc b/pycrosstalker/tools/__pycache__/Comparative_condition.cpython-312.pyc
diff --git a/pycrosstalker/tools/__pycache__/Single_Condition.cpython-311.pyc b/pycrosstalker/tools/__pycache__/Single_Condition.cpython-311.pyc
diff --git a/pycrosstalker/tools/__pycache__/Single_Condition.cpython-312.pyc b/pycrosstalker/tools/__pycache__/Single_Condition.cpython-312.pyc
diff --git a/pycrosstalker/tools/__pycache__/__init__.cpython-311.pyc b/pycrosstalker/tools/__pycache__/__init__.cpython-311.pyc
diff --git a/pycrosstalker/tools/__pycache__/__init__.cpython-312.pyc b/pycrosstalker/tools/__pycache__/__init__.cpython-312.pyc
diff --git a/pycrosstalker/tools/__pycache__/generate_report.cpython-311.pyc b/pycrosstalker/tools/__pycache__/generate_report.cpython-311.pyc
diff --git a/pycrosstalker/tools/__pycache__/generate_report.cpython-312.pyc b/pycrosstalker/tools/__pycache__/generate_report.cpython-312.pyc
diff --git a/pycrosstalker/tools/__pycache__/lrobject.cpython-311.pyc b/pycrosstalker/tools/__pycache__/lrobject.cpython-311.pyc
diff --git a/pycrosstalker/tools/__pycache__/lrobject.cpython-312.pyc b/pycrosstalker/tools/__pycache__/lrobject.cpython-312.pyc
diff --git a/pycrosstalker/tools/__pycache__/utils.cpython-311.pyc b/pycrosstalker/tools/__pycache__/utils.cpython-311.pyc
diff --git a/pycrosstalker/tools/__pycache__/utils.cpython-312.pyc b/pycrosstalker/tools/__pycache__/utils.cpython-312.pyc
diff --git a/pycrosstalker/tools/generate_report.py b/pycrosstalker/tools/generate_report.py
@@ -17,7 +17,7 @@ def analise_LR(input,
                 out_file=None, 
                 output_fmt="html_document", 
                 sel_columns=['source','target','gene_A','gene_B','type_gene_A','type_gene_B','MeanLR'], 
-                org='hsa', comparison=None, filtered_net=False, filename=None):
+                comparison=None, filtered_net=False, filename=None,save=True):
 
     """
     Core engine to generate report. Here we perform all the computation related to pyCrossTalkeR
@@ -44,7 +44,8 @@ def analise_LR(input,
         columns from data
     filename :
         filename prefix for output files (to be provided if not already present in AnnData object)
-
+    save:
+        Indicates if analysis file is saved or not
     Returns
     -------
     Rmarkdown report all objects from each step
@@ -75,7 +76,7 @@ def analise_LR(input,
     print("Network Analysis Done")
 
     print("Generating h5ad file with Analysed Results")
-    annData.write(os.path.join(out_path, annData.uns['pycrosstalker']['details']['filename'] + "_analysed.h5ad"))
-
+    if save:
+        annData.write(os.path.join(out_path, annData.uns['pycrosstalker']['details']['filename'] + "_analysed.h5ad"))
     return(annData)
Original file line number	Diff line number	Diff line change
Expand Up		@@ -34,7 +34,6 @@ You can install pyCrossTalkeR with the simple commands below:

		```
		pip install pycrosstallker

		```


Expand Down