Remove docker from PR

.github/workflows/ci.yml

@@ -214,37 +214,4 @@ jobs:
         run: bash tests/test_htsinfer_with_conda/test.local.sh
 
       - name: Run SRA downloads workflow
-        run: bash tests/test_sra_download_with_conda/test.local.sh
-
-  integration-docker:
-    needs:
-      - snakemake-graphs-format
-    runs-on: ubuntu-20.04
-    defaults:
-      run:
-        shell: bash -l {0}
-    steps:
-
-        - name: Checkout zarp repository
-          uses: actions/checkout@v4
-
-        - name: Setup miniconda & zarp env
-          uses: conda-incubator/setup-miniconda@v3
-          with:
-            python-version: "3.10"
-            mamba-version: "1"
-            channels: conda-forge
-            channel-priority: true
-            auto-update-conda: false
-            activate-environment: zarp
-            environment-file: install/environment.yml
-            auto-activate-base: false
-
-        - name: Update zarp env with dev. packages
-          run: mamba env update -p $CONDA_PREFIX -f install/environment.dev.yml
-
-        - name: Run test script
-          run: bash tests/test_integration_workflow_with_docker/test.local.sh
-
-        - name: Clean up
-          run: rm -rf data
+        run: bash tests/test_sra_download_with_conda/test.local.sh

README.md

@@ -75,11 +75,11 @@ The workflow was built and tested with `miniconda 4.7.12`.
 Other versions are not guaranteed to work as expected.
 
 Given that Miniconda has been installed and is available in the current shell the first
-dependency for ZARP is the [Mamba][mamba] package manager, which needs to be installed in
+dependency for ZARP is the [Mamba][mamba] package manager (version 1), which needs to be installed in
 the `base` conda environment with:
 
 ```bash
-conda install mamba -n base -c conda-forge
+conda install mamba=1 -n base -c conda-forge
 ```
 
 ## 3. Dependencies installation

docs/guides/usage.md

@@ -162,60 +162,4 @@ snakemake \
 
 However, this call will exit with an error, as not all parameters can be inferred from the example files. The argument `--keep-incomplete` makes sure the `samples_htsinfer.tsv` file can nevertheless be inspected. 
 
-After successful execution - if all parameters could be either inferred or were specified by the user - `[OUTDIR]/[SAMPLES_OUT]` should contain a populated table with parameters `seqmode`, `f1_3p`, `f2_3p`, `organism`, `libtype` and `index_size`.
-
-
-## Execution with Docker
-
-ZARP is optimised for Linux users as all packages are available via Conda or Apptainer (Singularity). For other systems like Mac OS X, they don't work especially due to the current transition from Intel to ARM processors (M series). Nevertheless we built a Docker container that can be used to run ZARP in such environments.
-
-1. Install Docker following the instructions [here](https://docs.docker.com/desktop/install/mac-install/)
-
-2. Pull the Docker image the contains the necessary dependencies
-```sh
-docker pull zavolab/zarp:1.0.0-rc.1
-```
-
-3. Create a directoty (e.g. `data`) and store all the files required for a run:
-    - The genome sequence fasta file
-    - The annotation gtf file
-    - The fastq files of your experiments
-    - The `rule_config.yaml` for the parameters
-    - The `samples.tsv` containing the metadata of your samples
-    - The `config.yaml` file with parameters. Below you can find an example file where you can see that it points to files in the `data` directory.
-        ```yaml
-        ---
-          # Required fields
-          samples: "data/samples_docker.tsv"
-          output_dir: "data/results"
-          log_dir: "data/logs"
-          cluster_log_dir: "data/logs/cluster"
-          kallisto_indexes: "data/results/kallisto_indexes"
-          salmon_indexes: "data/results/salmon_indexes"
-          star_indexes: "data/results/star_indexes"
-          alfa_indexes: "data/results/alfa_indexes"
-          # Optional fields
-          rule_config: "data/rule_config.yaml"
-          report_description: "No description provided by user"
-          report_logo: "../../images/logo.128px.png"
-          report_url: "https://zavolan.biozentrum.unibas.ch/"
-          author_name: "NA"
-          author_email: "NA"
-        ...
-        ```
-
-4. Execute ZARP as following:
-    ```sh
-    docker run \
-        --platform linux/x86_64 \
-        --mount type=bind,source=$PWD/data,target=/data \
-        zavolab/zarp:1.0.0-rc.1 \
-        snakemake \
-        -p \
-        --snakefile /workflow/Snakefile \
-        --configfile data/config.yaml \
-        --cores 4 \
-        --use-conda \
-        --verbose
-    ```
-    The command runs the Docker container `zavolab/zarp:1.0.0-rc.1` that we have pulled. It executes it as it would be done on a Linux platform `--platform linux/x86_64`. We use the `--mount` option to bind the local `data` directory that contains the input files with the `data` directory in the container. The pipeline is stored in the container in the path `/workflow/Snakefile`. Once ZARP is complete, the results will be stored in the `data/results` directory.
+After successful execution - if all parameters could be either inferred or were specified by the user - `[OUTDIR]/[SAMPLES_OUT]` should contain a populated table with parameters `seqmode`, `f1_3p`, `f2_3p`, `organism`, `libtype` and `index_size`.