Port remaining content out of readme, update URLs

Author: jeromekelleher

README.md

@@ -11,105 +11,8 @@ access.
 convenient and efficient access to the full Viridian dataset (alignments and metadata)
 in a single file using the [VCF Zarr specification](https://doi.org/10.1093/gigascience/giaf049).
 
-Please see the [preprint](https://www.biorxiv.org/content/10.1101/2023.06.08.544212v2)
-for details.
-
-## Installation
-
-Install sc2ts from PyPI:
-
-```
-python -m pip install sc2ts
-```
-
-This installs the minimum requirement to enable the
-[ARG analysis](#ARG-analysis-API) and [Dataset](#Dataset-API)s.
-To run [inference](#inference), you must install some extra
-dependencies using the 'inference' optional extra:
-
-```
-python -m pip install sc2ts[inference]
-```
-
-## ARG analysis API
-
-The sc2ts API provides two convenience functions to compute summary
-dataframes for the nodes and mutations in a sc2ts-output ARG.
-
-To see some examples, first download the (31MB) sc2ts inferred ARG
-from [Zenodo](https://zenodo.org/records/17558489/):
-
-```
-curl -O https://zenodo.org/records/17558489/files/sc2ts_viridian_v1.2.trees.tsz
-```
-
-We can then use these like
-
-```python
-import sc2ts
-import tszip
-
-ts = tszip.load("sc2ts_viridian_v1.2.trees.tsz")
-
-df_node = sc2ts.node_data(ts)
-df_mutation = sc2ts.mutation_data(ts)
-```
-
-See the [live demo](https://tskit.dev/explore/lab/index.html?path=sc2ts.ipynb)
-for a browser based interactive demo of using these dataframes for
-real-time pandemic-scale analysis.
-
-## Dataset API
-
-Sc2ts also provides a convenient API for accessing large-scale
-alignments and metadata stored in
-[VCF Zarr](https://doi.org/10.1093/gigascience/giaf049) format.
-
-Resources:
-
-- See this [notebook](https://github.com/jeromekelleher/sc2ts-paper/blob/main/notebooks/example_data_processing.ipynb)
-for an example in which we access the data variant-by-variant and
-which explains the low-level data encoding
-- See the [VCF Zarr publication](https://doi.org/10.1093/gigascience/giaf049)
-for more details on and benchmarks on this dataset.
-
-
-**TODO** Add some references to API documentation
-
-
-
-## Development
-
-To run the unit tests, use
-
-```
-python3 -m pytest
-```
-
-You may need to regenerate some cached test fixtures occasionaly (particularly
-if getting cryptic errors when running the test suite). To do this, run
-
-```
-rm -fR tests/data/cache/
-```
-
-and rerun tests as above.
-
-### Debug utilities
-
-The tree sequence files output during primary inference have a lot
-of debugging metadata, and there are some developer tools for inspecting
-this in the ``sc2ts.debug`` package. In particular, the ``ArgInfo``
-class has a lot of useful utilities designed to be used in a Jupyter
-notebook. Note that ``matplotlib`` is required for these. Use it like:
-
-```python
-import sc2ts.debug as sd
-import tskit
-
-ts = tskit.load("path_to_daily_inference.ts")
-ai = sd.ArgInfo(ts)
-ai # view summary in notebook
-```
-
+Please see the online [documentation](https://tskit.dev/sc2ts/docs) for details
+on the software
+and the [preprint](https://www.biorxiv.org/content/10.1101/2023.06.08.544212v2)
+for information on the method and the inferred ARG.
 

docs/_toc.yml

@@ -13,3 +13,6 @@ parts:
     chapters:
       - file: cli
       - file: api
+  - caption: Misc
+    chapters:
+      - file: development

docs/arg_analysis.md

@@ -1,2 +1,51 @@
 (sec_arg_analysis)=
 # ARG analysis
+
+
+## ARG analysis API
+
+The sc2ts API provides two convenience functions to compute summary
+dataframes for the nodes and mutations in a sc2ts-output ARG.
+
+To see some examples, first download the (31MB) sc2ts inferred ARG
+from [Zenodo](https://zenodo.org/records/17558489/):
+
+```
+curl -O https://zenodo.org/records/17558489/files/sc2ts_viridian_v1.2.trees.tsz
+```
+
+We can then use these like
+
+```python
+import sc2ts
+import tszip
+
+ts = tszip.load("sc2ts_viridian_v1.2.trees.tsz")
+
+df_node = sc2ts.node_data(ts)
+df_mutation = sc2ts.mutation_data(ts)
+```
+
+See the [live demo](https://tskit.dev/explore/lab/index.html?path=sc2ts.ipynb)
+for a browser based interactive demo of using these dataframes for
+real-time pandemic-scale analysis.
+
+## Dataset API
+
+Sc2ts also provides a convenient API for accessing large-scale
+alignments and metadata stored in
+[VCF Zarr](https://doi.org/10.1093/gigascience/giaf049) format.
+
+Resources:
+
+- See this [notebook](https://github.com/jeromekelleher/sc2ts-paper/blob/main/notebooks/example_data_processing.ipynb)
+for an example in which we access the data variant-by-variant and
+which explains the low-level data encoding
+- See the [VCF Zarr publication](https://doi.org/10.1093/gigascience/giaf049)
+for more details on and benchmarks on this dataset.
+
+
+**TODO** Add some references to API documentation
+
+
+

docs/development.md

@@ -0,0 +1,42 @@
+
+# Development
+
+To run the development dependencies use
+
+```
+python3 -m pip install .[dev]
+```
+
+To run the unit tests, use
+
+```
+python3 -m pytest
+```
+
+You may need to regenerate some cached test fixtures occasionaly (particularly
+if getting cryptic errors when running the test suite). To do this, run
+
+```
+rm -fR tests/data/cache/
+```
+
+and rerun tests as above.
+
+## Debug utilities
+
+The tree sequence files output during primary inference have a lot
+of debugging metadata, and there are some developer tools for inspecting
+this in the ``sc2ts.debug`` package. In particular, the ``ArgInfo``
+class has a lot of useful utilities designed to be used in a Jupyter
+notebook. Note that ``matplotlib`` is required for these. Use it like:
+
+```python
+import sc2ts.debug as sd
+import tskit
+
+ts = tskit.load("path_to_daily_inference.ts")
+ai = sd.ArgInfo(ts)
+ai # view summary in notebook
+```
+
+

pyproject.toml

@@ -21,6 +21,13 @@ dependencies = [
 ]
 dynamic = ["version"]
 
+[project.urls]
+Homepage = "https://tskit.dev/sc2ts"
+Documentation = "https://tskit.dev/sc2ts/docs/"
+"Bug Tracker" = "https://github.com/tskit-dev/sc2ts/issues"
+GitHub = "https://github.com/tskit-dev/sc2ts/"
+
+
 [project.scripts]
 sc2ts = "sc2ts.cli:cli"