updated installation docs, updated reference to Nat Biotech

README.md

@@ -1,22 +1,46 @@
 # TACCO: Transfer of Annotations to Cells and their COmbinations
 
-TACCO is a python framework for working with categorical and compositional annotations for high-dimensional observations, in particular for transferring annotations from single cell to spatial transcriptomics data. TACCO comes with an extensive ever expanding [documentation](https://simonwm.github.io/tacco/) and a set of [example notebooks](https://github.com/simonwm/tacco_examples). If TACCO is useful for your research, you can cite [bioRxiv (2022)](https://doi.org/10.1101/2022.10.02.508471).
+TACCO is a python framework for working with categorical and compositional annotations for high-dimensional observations, in particular for transferring annotations from single cell to spatial transcriptomics data. TACCO comes with an extensive ever expanding [documentation](https://simonwm.github.io/tacco/) and a set of [example notebooks](https://github.com/simonwm/tacco_examples). If TACCO is useful for your research, you can cite [Nat Biotechnol (2023)](https://doi.org/10.1038/s41587-023-01657-3).
 
 ## How to install TACCO
 
+### Clean
+
 The simplest way to install TACCO is to create a clean environment with `conda` using the `environment.yml` file from the TACCO repository:
 
 ```
 conda env create -f "https://raw.githubusercontent.com/simonwm/tacco/master/environment.yml"
 ```
 (For older versions of `conda` one needs to download the `environment.yml` and use the local file for installation.)
 
-To install TACCO in an already existing environment, one can use `pip` to directly install the latest release from github:
+### Conda
+
+To install TACCO in an already existing environment, use `conda` to install from the `conda-forge` channel:
+
+```
+conda install -c conda-forge tacco
+```
+
+### Pip
+
+It is also possible to install from pypi via `pip`:
+
+```
+pip install tacco
+```
+
+This is however not recommended. Unlike `conda`, `pip` cannot treat python itself as a package, so if you start with the wrong python version, you will run into errors with dependencies (e.g. at the time of writing, `mkl-service` is not available for python 3.10 and `numba` not for 3.11).
+
+### Github
+
+To access the most recent pre-release versions it is also possible to pip-install directly from github:
 
 ```
 pip install tacco@git+https://github.com/simonwm/tacco.git
 ```
 
+Obviously, this is not recomended for production environments.
+
 ## How to use TACCO
 
 TACCO features a fast and straightforward API for the compositional annotation of one dataset, given as an anndata object `adata`, with a categorically annotated second dataset, given as an anndata object `reference`. The annotation is wrapped in a single function call

docsource/references.rst

@@ -29,9 +29,9 @@ References
    *GOATOOLS: A Python library for Gene Ontology analyses*,
    `Scientific Reports <https://www.nature.com/articles/s41598-018-28948-z>`__.
 
-.. [Mages23] Mages *et al.* (2022),
-   *TACCO: Unified annotation transfer and decomposition of cell identities for single-cell and spatial omics*,
-   `BioRxiv <https://doi.org/10.1101/2022.10.02.508471>`__.
+.. [Mages23] Mages *et al.* (2023),
+   *TACCO unifies annotation transfer and decomposition of cell identities for single-cell and spatial omics*,
+   `Nature Biotechnology <https://doi.org/10.1038/s41587-023-01657-3>`__.
 
 .. [Nitzan19] Nitzan *et al.* (2019),
    *Gene expression cartography*,

environment.yml

@@ -22,8 +22,5 @@ dependencies:
   - scikit-learn
   - threadpoolctl
   - pyamg
-  - pip # for pip installing tacco
-  - git # for pip installing tacco from github
-  - pip:
-     - git+https://github.com/simonwm/tacco.git
+  - tacco