Split out common installation from tutorials

.github/workflows/tutorials.yaml

@@ -9,7 +9,7 @@ concurrency:
   cancel-in-progress: ${{ github.ref != 'refs/heads/main' }}
 
 jobs:
-  build_n_push:
+  installer:
     runs-on: ubuntu-latest
 
     defaults:
@@ -20,6 +20,10 @@ jobs:
       - name: Checkout repository
         uses: actions/checkout@v3
         with:
+            sparse-checkout: |
+                docs
+                tests
+            sparse-checkout-cone-mode: false
             lfs: false
 
       - name: Install conda environment dependencies
@@ -29,7 +33,7 @@ jobs:
           miniforge-variant: Mambaforge
           python-version: "3.11"
           mamba-version: "*"
-          channels: conda-forge,bioconda #,defaults # see: https://github.com/conda-forge/status/issues/144
+          channels: conda-forge,bioconda
           channel-priority: strict
           activate-environment: JupyText
           auto-update-conda: true
@@ -39,14 +43,17 @@ jobs:
         run: |
           python -m ipykernel install --user
 
-      - name: Run notebooks
+      - name: Run installation notebooks
         working-directory: ./docs
-        run: ./convert.sh branch
+        run: ./convert.sh --branch *_install.md
 
-      - uses: actions/upload-artifact@v3
+      - name: Keep installation
+        uses: actions/upload-artifact@v3
         with:
-          name: JupyterNotebooks
-          path: ./docs/*.ipynb
+          name: VPipeInstallation
+          path: ./vp-analysis
+
+
       # - name: Publish
       #   uses: peaceiris/actions-gh-pages@v3
       #   with:

docs/tutorial_0_install.md

@@ -0,0 +1,106 @@
+---
+jupyter:
+  jupytext:
+    cell_metadata_filter: -all
+    formats: ipynb,md
+    text_representation:
+      extension: .md
+      format_name: markdown
+      format_version: '1.3'
+      jupytext_version: 1.14.5
+  kernelspec:
+    display_name: Python 3
+    language: python
+    name: python3
+---
+
+<!-- markdownlint-configure-file { "MD010": { "ignore_code_languages" : [ "tsv", "bash" ] } } -->
+# V-Pipe Installation
+
+V-pipe is a workflow designed for the analysis of next generation sequencing (NGS) data from viral pathogens. It produces a number of results in a curated format (e.g., consensus sequences, SNV calls, local/global haplotypes). V-pipe is written using the Snakemake workflow management system.
+
+The present tutorial will show you how to install V-pipe and the dependencies required to start using it - bioconda, conda-froge mamba and snakemake - before continuing with other tutorials and analyse virus data.
+
+## Requirements
+
+V-pipe is optimized for Linux or Mac OS systems, and bioconda isn't supported on Windows. Therefore, we recommend users with a Windows system to [install WSL2](https://learn.microsoft.com/en-us/windows/wsl/install) - this is not a full virtual machine but rather a way to run Windows and Linux cooperatively at the same time.
+
+
+## Organizing Software
+
+We will organise our software in the following tree structure, which will be reused in all subsequent tutorials:
+
+```text
+📁 [HOME]
+└───📁vp-analysis
+    ├───📁V-pipe      # V-pipe checked out from Github
+    ├───📁Miniforge3  # bioconda + conda-forge + mamba + Snakemake
+    ├───📁work        # work directories
+    ├───📁work-tests  #  …
+    └───📁 …          #  …
+```
+
+- `vp-analysis` is the main directory where we will store everything.
+- `Miniforge3` is the directory where conda will be installed including the dependencies to start using V-pipe.
+- `V-pipe` is the directory where V-pipe's own code will be downloaded from GitHub
+- finally, each analysis of virus data will be performed into directory like `work…`, which holds the configuration and the sequencing data for that particular analysis.
+
+
+## Install V-pipe and conda from scratch
+
+V-pipe uses the [Bioconda](https://bioconda.github.io/) bioinformatics software repository for all its pipeline components. The pipeline itself is implemented using [Snakemake](https://snakemake.readthedocs.io/en/stable/).
+
+For advanced users: If your are fluent with these tools, see [below](#fluent-users)
+
+In this present short tutorial you will learn how to setup a workflow for the various examples in the analysis tutorials.
+
+To deploy V-pipe, you can use the installation script with the following parameters:
+
+```bash
+curl -O 'https://raw.githubusercontent.com/cbg-ethz/V-pipe/master/utils/quick_install.sh'
+bash quick_install.sh -p vp-analysis -w work
+```
+
+> **Note**:
+> * using `-p` specifies the subdirectory where to download and install snakemake and V-pipe
+> * using `-w` will create a working directory and populate it. It will colloquial the references and the default `config/config.yaml`, and create a handy `vpipe` short-cut script to invoke `snakemake`.
+> * an additional option `-b` (not demonstrated above) allows to install a spefic branch or tagged version. If nothing is specified, the master branch will be installed.
+
+If you get `zsh: permission denied: ./quick_install.sh`, run `chmod +x quick_install.sh` this gives the necessary permissions.
+
+
+**Tip:** To create and populate other new working directories, you can call init_project.sh from within the new directory:
+
+```bash
+cd vp-analysis/
+
+mkdir -p working_2
+cd working_2
+../V-pipe/init_project.sh
+
+# now edit config.yaml, samples.tsv, run your analysis etc.
+
+cd -
+```
+
+### Analyse data
+
+Now that you have setup the software necessary to start using V-pipe, you can follow with one of the tutorials showing you analysis of viral sequencing data:
+
+- [tutorial_hiv.md](tutorial_hiv.md): uses HIV test data
+- [tutorial_sarscov2.md](tutorial_sarscov2.md): uses SARS-CoV-2 data from a publication
+
+
+## Fluent users
+
+For advanced users: If your are fluent with these tools, you can:
+
+* directly download and install [bioconda](https://bioconda.github.io/user/install.html) and [snakemake](https://snakemake.readthedocs.io/en/stable/getting_started/installation.html#installation-via-conda),
+* specifiy your V-pipe configuration, and start using V-pipe
+
+Use `--use-conda` to [automatically download and install](https://snakemake.readthedocs.io/en/stable/snakefiles/deployment.html#integrated-package-management) any further pipeline dependencies. Please refer to the documentation for additional instructions.
+
+
+### Reusing an existing conda installation
+
+[TO BE CONTINUED]