[DOC] Fix indentations (must have 4 spaces for mkdocs to render prope…

…rly) (#1367)

Also did some consistency fixes in casing and punctuations.

docs/Atlases.md

@@ -78,9 +78,9 @@ It was built on anatomical MRI of 24 healthy subjects from which 74 cortical ROI
 It is possible to run the [`t1-volume`](../T1_Volume) and [`pet-volume`](../PET_Volume) pipelines using a custom parcellation.
 To do so:
 
-- Install Clinica following the [developer instructions](../Installation/#install-clinica);
+- Install Clinica following the [developer instructions](../Installation/#install-clinica).
 
-  - In the `<clinica>/clinica/utils/atlas.py` file, modify the following two elements:
+- In the `<clinica>/clinica/utils/atlas.py` file, modify the following two elements:
       - The label of the volume atlas that will be stored in CAPS filename(s):
 
       ```python

docs/Pipelines/Stats_Surface.md

@@ -44,9 +44,9 @@ where:
 - `CAPS_DIRECTORY` is the folder containing the results of the [`t1-freesurfer`](./T1_FreeSurfer.md) or [`pet-surface`](./PET_Surface.md) pipeline and the output of the present command, both in a [CAPS hierarchy](../CAPS/Introduction.md).
 - `GROUP_LABEL` is a string defining the group label for the current analysis, which helps you keep track of different analyses.
 - The third positional argument defines the type of surface-based feature. It can be:
-  - `t1-freesurfer` for cortical thickness
-  - `pet-surface` for projected PET data
-  - `custom-pipeline` for you own data in CAPS directory (see below for details)
+    - `t1-freesurfer` for cortical thickness
+    - `pet-surface` for projected PET data
+    - `custom-pipeline` for you own data in CAPS directory (see below for details)
 - The fourth positional argument is a string defining the type of analysis of your model. It can be either `group_comparison` or `correlation`.
 - `SUBJECT_VISITS_WITH_COVARIATES_TSV` is a TSV file containing a list of subjects with their sessions and all the covariates and factors in your model (the content of the file is explained in the [Example](#comparison-analysis) subsection).
 - `CONTRAST` is a string defining the contrast matrix or the variable of interest for the [GLM](../glossary.md#glm). For example `group`, `sex`, or `age`.

docs/WhatIsClinica.md

@@ -11,16 +11,16 @@ Future versions will include more extensive support of genotyping data and clini
 
 ## What are the main features of Clinica?
 
-- Neuroimaging data analysis
-  - Anatomical MRI
-  - Diffusion MRI
-  - [PET](glossary.md#pet)
+- Neuroimaging data analysis:
+    - anatomical MRI
+    - diffusion MRI
+    - [PET](glossary.md#pet)
 - Statistical analysis
 - Machine learning
 - Data management made easy:
-  - Standardized data structures for inputs
-  - Standardized data structures for outputs
-  - Conversion of datasets
+    - standardized data structures for inputs
+    - standardized data structures for outputs
+    - conversion of datasets
 
 ## Which technologies underlie Clinica?