update README, CITATION and pypi publishing workflow in doc branch

.github/workflows/publish.yml

@@ -0,0 +1,25 @@
+name: Publish to PyPI
+
+on:
+  release:
+    types: [published]
+
+jobs:
+  pypi-publish:
+    name: Build and publish to PyPI
+    runs-on: ubuntu-latest
+    permissions:
+      id-token: write  # Mandatory for Trusted Publishing
+      contents: read
+    steps:
+      - uses: actions/checkout@v4
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.10"
+      - name: Install Poetry
+        run: pip install poetry
+      - name: Build package
+        run: poetry build
+      - name: Publish package
+        uses: pypa/gh-action-pypi-publish@release/v1

CITATION.cff

@@ -7,6 +7,6 @@ authors:
   given-names: "James"
 title: "NicheSphere"
 version: 1.0.0
-doi: 10.5281/zenodo.XXXXX  # Update this AFTER you get your DOI from Zenodo
-date-released: 2026-02-24  # Use today's date
-url: "https://github.com/CostaLab/NicheSphere"
+doi: 10.5281/zenodo.1875671
+date-released: 2026-02-24
+url: "https://github.com/CostaLab/NicheSphere"

README.md

@@ -2,7 +2,7 @@
 
 # NicheSphere
 
-[![DOI](https://zenodo.org)](https://doi.org)
+[![DOI](https://zenodo.org/badge/685916590.svg)](https://doi.org/10.5281/zenodo.18756710)
 
 NicheSphere is an sc-verse compatible Python library which allows the user to find differential co-localization domains / niches based on cell type pair co-localization probabilities in different conditions. Cell type pair co-localization probabilities can be obtained in different ways, for example, through deconvolution of spatial transcriptomics / PIC-seq data (getting the probabilities of finding each cell type in each spot / multiplet) ; or counting nearest neighbors of each type for each cell in single cell spatial data like MERFISH or CODEX.