update doc with change in info and metrics command

labgem · Dec 13, 2023 · 2de0f03 · 2de0f03
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diff --git a/docs/index.md b/docs/index.md
@@ -45,7 +45,7 @@ RGPs from different genomes are next grouped in spots of insertion based on thei
 Those RGPs can be further divided in conserved modules by panModule ([Bazin et al. 2021](https://doi.org/10.1101/2021.12.06.471380)). Those conserved modules correspond to groups of cooccurring and colocalized genes that are gained or lost together in the variable regions of the pangenome.
 
 
-
+<!-- 
 [//]: # (```{toctree})
 
 [//]: # (:caption: 'Tutorial:')
@@ -61,7 +61,7 @@ Those RGPs can be further divided in conserved modules by panModule ([Bazin et a
 
 [//]: # (tutorial/AnalyseRGP)
 
-[//]: # (```)
+[//]: # (```) -->
 
 ```{toctree}
 :caption: 'User Guide:'

diff --git a/docs/user/PangenomeAnalyses/pangenomeAnalyses.md b/docs/user/PangenomeAnalyses/pangenomeAnalyses.md
@@ -27,11 +27,17 @@
 ```{include} ./pangenomeStat.md
 ```
 
-```{include} ./pangenomeMetric.md
-```
-
 ```{include} ./pangenomeFigures.md
 ```
 
 ```{include} ./pangenomeGraphOut.md
 ```
+
+## Pangenome metrics
+```{include} ./pangenomeMetric.md
+```
+
+## Pangenome info
+
+```{include} ./pangenomeInfo.md
+```
diff --git a/docs/user/PangenomeAnalyses/pangenomeMetric.md b/docs/user/PangenomeAnalyses/pangenomeMetric.md
@@ -1,17 +1,37 @@
-### Pangenome metrics
+<!-- # Metrics -->
 
+After computing a pangenome, it's interesting to get some metrics about it.
+The aim of the `metrics` subcommand is to compute comprehensive metrics describing the pangenome.
 
-#### Genomic fluidity
+All the metrics computed are saved in the pangenome file and 
+are displayed by the `info` subcommand with the flag `--content`.
+
+
+### Genomic fluidity
 
 The genomic fluidity is described as *a robust metric to categorize the
 gene-level similarity among groups of sequenced isolates.* 
 [more information here](https://bmcgenomics.biomedcentral.com/articles/10.1186/1471-2164-12-32)
 
 We add the possibility to get genomic fluidity for all the pangenome or 
-for specific partition. The genomic fluidity is computable like that (with below an example result):
+for specific partition. The genomic fluidity is computable like that :
+
 ```bash
 ppanggolin metrics -p pangenome --genome_fluidity
-...
-Genomes fluidity: all=0.026, shell=0.477, cloud=0.045, accessory=0.554
+
+```
+
+```yaml
+Genomes_fluidity:
+    all: 0.139
+    shell: 0.527
+    cloud: 0.385
+    accessory: 0.62
 ```
-*all* correspond to all the family in the pangenome (core and accessory)
+*all* correspond to all the family in the pangenome (core and accessory)
+
+
+```{note}
+At the moment, only the fluidity is computed by the `metrics` command. But we migth add other metrics in the future. If you have some idea of metric describing the pangenome, please open an issue ! 
+```
+
diff --git a/docs/user/practicalInformation.md b/docs/user/practicalInformation.md
@@ -12,6 +12,13 @@ Once the pangenome is established, including gene clustering, partitioning, opti
 PPanGGOLiN utilizes the [pytable](https://www.pytables.org/index.html) Python library for handling the pangenome HDF-5 file. While graphical user interface tools like ['ViTables'](https://vitables.org/index.html) allow manual exploration and editing of the file, it's cautioned against, as it may compromise compatibility with PPanGGOLiN.
 
 
+You can use the command `info` to get comprehensive insights into the contents and construction process of a pangenome file. 
+
+```bash
+ppanggolin info -p pangenome.h5
+```
+
+
 ## Required computing resources
 
 Most of PPanGGOLiN's commands should be run with as many CPUs as you can give them by using the --cpu option as PPanGGOLiN's speed increases relatively well with the number of CPUs. 
@@ -49,7 +56,6 @@ Finaly, you can also save PPanGGOLiN logs in a file by indicating its path with
 
 ## Configuration file
 
-
 Advanced users can provide a configuration file containing any or all parameters to PPanGGolin commands. 
 This feature is particularly useful for workflow commands such as `workflow`, `all`, `panrgp`, and `panmodule`, as it allows for the specification of all parameters for each subcommand launched in a workflow. 
 Additionally, a configuration file can be used to reuse a specific set of parameters across multiple pangenomes.