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Commit 2f48e8ce authored by Alex Kanitz's avatar Alex Kanitz
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test: fix local execution test

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README.md
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# mir-prepare-annotation
[Snakemake] workflow to download and prepare the necessary files for smallRNA-seq related pipelines, currently [mir-map](https://git.scicore.unibas.ch/zavolan_group/pipelines/mir-map) and [mir-quant](https://git.scicore.unibas.ch/zavolan_group/pipelines/mir-quant).
[Snakemake] workflow to download and prepare the necessary files for
smallRNA-seq related pipelines
[mir-map](https://git.scicore.unibas.ch/zavolan_group/pipelines/mir-map)
and
[mir-quant](https://git.scicore.unibas.ch/zavolan_group/pipelines/mir-quant).
The scheme below is a visual representation of an example run of the
workflow:
workflow:
> ![workflow_dag](images/rule_graph.svg)
......@@ -18,10 +22,19 @@ move into it with:
git clone ssh://git@git.scicore.unibas.ch:2222/zavolan_group/pipelines/mir-prepare-annotation.git
cd mir-prepare-annotation
```
### Setting up a virtual environment
Workflow dependencies can be conveniently installed with the [Conda][conda]
package manager. We recommend that you install [Miniconda][miniconda-installation] for your system.
package manager. We recommend that you install
[Miniconda][miniconda-installation] for your system.
For improved reproducibility and reusability of the workflow, as well as an
easy means to run it on a high performance computing (HPC) cluster managed,
e.g., by [Slurm][slurm], almost all steps of the workflow run in their own
container. As a consequence, running this workflow has very few individual
dependencies. It does, however, require that the container engine
[Singularity][singularity] is installed.
Create and activate the environment with necessary dependencies with conda:
......@@ -30,69 +43,83 @@ conda env create -f environment.yml
conda activate mir_pipelines
```
For improved reproducibility and reusability of the workflow, as well as an
easy means to run it on a high performance computing (HPC) cluster managed,
e.g., by [Slurm][slurm], each individual step of the workflow runs in its own container.
Specifically, containers are created out of [Singularity][singularity] images
built for each software used within the workflow. As a consequence, running
this workflow has very few individual dependencies. It does, however, require
that [Singularity][singularity] to be installed.
> **NOTE:** If `singularity` is already installed on your system, which is,
> e.g., frequently the case in HPC environments, make sure to comment out or
> delete the corresponding line from `environment.yml` prior to the creation
> of the Conda environment. This will avoid conflicts.
### Testing your installation
Several tests are prepared to check the integrity of the workflow.
> **NOTE:** `Singularity` is automatically loaded on the sciCORE system. To avoid conflicts, comment out or delete `singularity` in the file `environment.yml` before you create the virtual environment.
Change into the test directory:
## Testing
Several tests are prepared to check the integrity of the workflow.
Move into `test/` directory:
```bash
cd test/
```
## DAG and rule graph
Execute the following commands to generete DAG and rule graph images. Outputs will be found in `images/` folder.
#### DAG and rule graph
Execute the following commands to generete DAG and rule graph images. Outputs
will be found in `images/` folder.
```bash
./test_dag.sh
./test_rule_graph.sh
```
### Run workflow on local machine
#### Run workflow on local machine
Execute the following command to run the test workflow on your local machine:
```bash
./test_workflow_local.sh
```
### Run workflow via Slurm
Execute the following command to run the test workflow on a Slurm-managed high-performance computing (HPC) cluster::
#### Run workflow via Slurm
Execute the following command to run the test workflow on a Slurm-managed
high-performance computing (HPC) cluster:
```bash
./test_workflow_slurm.sh
```
## Usage
Assuming that you are currently inside the repository's root directory...
Assuming that you are currently inside the repository's root directory, change
to the execution directory:
* To run the pipeline with your own samples:
```bash
cd RUN_JOB
```
Before running the pipeline adjust the parameters in `config.yaml`file.
Before running the pipeline adjust the parameters in file `config.yaml`. We
recommend that you create a copy of it for each run.
To start pipeline execution locally:
```bash
./run_workflow_local.sh
```
To start pipeline execution in Slurm:
> *Recommended due to resources needs*
To start pipeline execution via Slurm:
```bash
./run_workflow_slurm.sh
```
After succesfully execution of the workflow results and logs outputs will be found in `results/` and `logs/` directories.
> **NOTE:** Depending on the configuration of your Slurm installation or if using a different workflow manager,
> you may need to adapt file `cluster.json` (located in root directory) and the arguments to options `--config` and `--cores` in file
> `run_workflow_slurm.sh`, located in RUN_JOB directory. Consult the manual of your workload manager as well as the section of the
> Snakemake manual dealing with [cluster execution].
> *This is strongly recommended due to excessive resource needs of some tools!*
After succesful execution of the workflow, results and logs will be found in
`results/` and `logs/` directories, respectively.
> **NOTE:** Depending on the configuration of your Slurm installation or if
> using a different batch scheduling system, you may need to adapt file
> `cluster.json` (located in root directory) and the arguments to options
> `--config` and `--cores` in file `run_workflow_slurm.sh`, located in the
> `RUN_JOB` directory. Consult the manual of your batch scheduling system, as
> well as the section of the Snakemake manual dealing with [cluster execution].
[conda]: <https://docs.conda.io/projects/conda/en/latest/index.html>
[cluster execution]: <https://snakemake.readthedocs.io/en/stable/executing/cluster-cloud.html#cluster-execution>
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images/rule_graph.svg
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images/workflow_dag.svg
+ 96
− 74
View file @ 2f48e8ce
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<!-- 7&#45;&gt;3 -->
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<g id="node10" class="node"><title>9</title>
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test/expected_output.files
+ 1
− 2
View file @ 2f48e8ce
......@@ -6,5 +6,4 @@ results/homo_sapiens/GRCh38.98_chrY/gene_annotations.filtered.gtf
results/homo_sapiens/GRCh38.98_chrY/exons.gtf
results/homo_sapiens/GRCh38.98_chrY/transcriptome.fa
results/homo_sapiens/GRCh38.98_chrY/exons.bed
results/homo_sapiens/GRCh38.98_chrY/headerOfCollapsedFasta.sam
results/homo_sapiens/GRCh38.98_chrY/genome_index_segemehl.idx
\ No newline at end of file
results/homo_sapiens/GRCh38.98_chrY/genome_index_segemehl.idx
test/expected_output.md5
+ 1
− 2
View file @ 2f48e8ce
......@@ -6,5 +6,4 @@ f37a213f94d11bf2260f50f2c9f199d2 results/homo_sapiens/GRCh38.98_chrY/genome.pro
6fe52e2e126ef2e0c368fb1bf267f453 results/homo_sapiens/GRCh38.98_chrY/exons.gtf
5ab1c2f39ab35fabc6673c73beb3097b results/homo_sapiens/GRCh38.98_chrY/transcriptome.fa
51ac61c61825929f8f05c4b4f821f04d results/homo_sapiens/GRCh38.98_chrY/exons.bed
7027e0b45c8e46ef79f1cb234fa3b839 results/homo_sapiens/GRCh38.98_chrY/headerOfCollapsedFasta.sam
11b0b7c50160aa8837dd92eda516c124 results/homo_sapiens/GRCh38.98_chrY/genome_index_segemehl.idx
\ No newline at end of file
11b0b7c50160aa8837dd92eda516c124 results/homo_sapiens/GRCh38.98_chrY/genome_index_segemehl.idx
test/test_workflow_local.sh
+ 2
− 2
View file @ 2f48e8ce
......@@ -3,8 +3,8 @@
# Tear down test environment
cleanup () {
rc=$?
#rm -rf .snakemake/
#rm -rf logs/
rm -rf .snakemake/
rm -rf logs/
rm -rf results/
cd $user_dir
echo "Exit status: $rc"
......
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