Fix small rendering issues

docs/README.md

@@ -14,11 +14,11 @@ The workflow is developed in [Snakemake][snakemake], a widely used workflow mana
 
 ## How does it work?
 
-ZARP requires conda or mamba to install the basic dependencies. Each individual step of the workflow run either in its own Apptainer (Singularity) container or in its own Conda virtual environment.
+ZARP requires Conda or Mamba to install the basic dependencies. Each individual step of the workflow runs either in its own Apptainer (Singularity) container or in its own Conda virtual environment.
 
 Once the installation is complete, you fill in a [config.yaml](https://github.com/zavolanlab/zarp/blob/dev/tests/input_files/config.yaml) file with parameters and a [samples.tsv](https://github.com/zavolanlab/zarp/blob/dev/tests/input_files/samples.tsv) file with sample specific information. You can easily trigger ZARP by making a call to snakemake with the appropriate parameters.
 
-The pipeline can be executed in different systems or HPC clusters. ZARP generates multiple output files that help you Quality Control (QC) your data and proceed with downstream analyses. Apart from running the main ZARP workflow, you can also run a second pipeline that pulls sequencing sample data from the Sequence Read Archive (SRA), and a third pipeline that populates a file with the samples and infers missing metadata.
+The pipeline can be executed in different systems or High Performance Computing (HPC) clusters. ZARP generates multiple output files that help you Quality Control (QC) your data and proceed with downstream analyses. Apart from running the main ZARP workflow, you can also run a second pipeline that pulls sequencing sample data from the Sequence Read Archive (SRA), and a third pipeline that populates a file with the samples and infers missing metadata.
 
 ## How to cite
 

docs/guides/installation.md

@@ -125,7 +125,7 @@ After installing Singularity, install the remaining dependencies with:
 mamba env create -f install/environment.yml
 ```
 
-### As root user on Linux
+**As root user on Linux**
 
 If you have a Linux machine, as well as root privileges, (e.g., if you plan to
 run the workflow on your own computer), you can execute the following command
@@ -135,17 +135,17 @@ to include Singularity in the Conda environment:
 mamba env update -f install/environment.root.yml
 ```
 
-## 5. Activate ZARP environment
+### 5. Activate ZARP environment
 
 Activate the Conda environment with:
 
 ```bash
 conda activate zarp
 ```
 
-## 6. Optional installation steps
+### 6. Optional installation steps
 
-### Install test dependencies
+#### Install test dependencies
 
 Most tests have additional dependencies. If you are planning to run tests, you
 will need to install these by executing the following command _in your active
@@ -155,7 +155,7 @@ Conda environment_:
 mamba env update -f install/environment.dev.yml
 ```
 
-### Run installation tests
+#### Run installation tests
 
 We have prepared several tests to check the integrity of the workflow and its
 components. These can be found in subdirectories of the `tests/` directory. 
@@ -167,24 +167,27 @@ Execute one of the following commands to run the test workflow
 on your local machine:
 
 
-#### Test workflow on local machine with **Singularity**:
+##### Test workflow on local machine with **Singularity**:
+
 ```bash
 bash tests/test_integration_workflow/test.local.sh
 ```
-#### Test workflow on local machine with **Conda**:
+
+##### Test workflow on local machine with **Conda**:
+
 ```bash
 bash tests/test_integration_workflow_with_conda/test.local.sh
 ```
 Execute one of the following commands to run the test workflow 
 on a [Slurm][slurm]-managed high-performance computing (HPC) cluster:
 
- #### Test workflow with **Singularity**:
+##### Test workflow with **Singularity**:
 
 ```bash
 bash tests/test_integration_workflow/test.slurm.sh
 ```
 
-#### Test workflow with **Conda**:
+##### Test workflow with **Conda**:
 
 ```bash
 bash tests/test_integration_workflow_with_conda/test.slurm.sh