doc update

Author: quentinblampey

CHANGELOG.md

@@ -2,8 +2,14 @@
 
 ### Added
 
+- Tutorial on CLI usage
+- Tutorial on image alignment with the Xenium Explorer
 - Multi-step segmentation ([#8](https://github.com/gustaveroussy/sopa/issues/8))
 - Tutorial for multi-step segmentation and custom segmentation
+- Improved installation guide
+
+### Fix
+- CLI issue (missing file) when used without Snakemake
 
 ### Change
 

docs/cli.md

@@ -91,7 +91,7 @@ $ sopa aggregate [OPTIONS] SDATA_PATH
 * `--min-transcripts INTEGER`: Cells with less transcript than this integer will be filtered  [default: 0]
 * `--min-intensity-ratio FLOAT`: Cells whose mean channel intensity is less than `min_intensity_ratio * quantile_90` will be filtered  [default: 0]
 * `--image-key TEXT`: Optional image key of the SpatialData object. By default, considers the only one image. It can be useful if another image is added later on
-* `--method-name TEXT`: If segmentation was performed with a generic method, this is the name of the method used.  [required]
+* `--method-name TEXT`: If segmentation was performed with a generic method, this is the name of the method used.
 * `--help`: Show this message and exit.
 
 ### `sopa annotate`

docs/getting_started.md

@@ -68,7 +68,7 @@ conda activate sopa
 pip install -e ".[snakemake,cellpose,baysor,tangram]"
 ```
 
-Now, follow our [snakemake tutorial](../tutorials/snakemake) to get started.
+Now, follow our [snakemake tutorial](../tutorials/snakemake) to run your first pipeline.
 
 !!! Note
     You can also use a separate environment for `snakemake`. In this case, you don't need to install the `'snakemake'` extra when installing `sopa`. But you may still need to install other extras, for instance `'cellpose'` if you plan to run Cellpose.

docs/tutorials/snakemake.md

@@ -26,7 +26,7 @@ Note the relative path of your config since you'll need it later, e.g. `config/m
 2. Then, activate your environment that has the snakemake command, and go to the `workflow` directory inside the `sopa` directory that you cloned earlier:
 ```sh
 conda activate sopa    # or an environment that has `snakemake`
-cd sopa/workflow       # your own personal path to the workflow directory
+cd workflow            # run this at the root of the 'sopa' directory
 ```
 
 1. You can either execute the pipeline locally, or on a high-performance-cluster (choose the right option below)
@@ -69,7 +69,7 @@ Make sure you have setup everything as detailed in this tutorial, and then run t
     Make sure you have installed sopa with the Cellpose extra
     ```sh
     conda activate sopa    # or an environment that has `snakemake`
-    cd sopa/workflow       # your own personal path to the workflow directory
+    cd workflow            # run this at the root of the 'sopa' directory
 
     # you can replace tuto.zarr by another path where the data will be saved
     snakemake --config data_path=. sdata_path=tuto.zarr --configfile=config/toy/uniform_cellpose.yaml --cores 1 --use-conda
@@ -79,7 +79,7 @@ Make sure you have setup everything as detailed in this tutorial, and then run t
     Make sure you have installed sopa with the Baysor extra, and that you have installed the `baysor` command
     ```sh
     conda activate sopa    # or an environment that has `snakemake`
-    cd sopa/workflow       # your own personal path to the workflow directory
+    cd workflow            # run this at the root of the 'sopa' directory
 
     # replace tuto.zarr by the path where you want the data to be saved
     snakemake --config data_path=. sdata_path=tuto.zarr --configfile=config/toy/uniform_baysor.yaml --cores 1 --use-conda