Conda/Mamba

For reproducible analysis, DamMapper uses Conda environments in the Snakemake workflow.

Please follow the instructions here for a detailed guide to install Conda/Mamba.

Snakemake

To install Snakemake create the following environment with Mamba:

$ mamba create -n snakemake snakemake=8.13

Activate the environment as follows:

$ conda activate snakemake

If you want to deploy Snakemake on an HPC system using slurm also run:

$ pip install snakemake-executor-plugin-slurm

Apptainer

A pre-build Docker image is available that contains Conda environments for all the rules in the workflow. This allows for the containerization of the entire workflow using Apptainer.

Apptainer might already be available on your HPC system, but to install it locally follow these instructions.

It is highly recommended to run the workflow using the --use-conda --use-apptainer flags.

Snakefetch

The easiest way to obtain the DamMapper workflow code is to use snakefetch.

To install snakefetch, run:

$ pip install snakefetch

Workflow installation

Using snakefetch:

$ snakefetch --outdir /path/to/analysis --repo-version v0.5.0 --url https://github.com/niekwit/damid-seq
Downloading archive file for version v0.5.0 from https://github.com/niekwit/damid-seq...
Extracting config and workflow directories from tar.gz file to /path/to/analysis...
Done!
$ tree /path/to/analysis
.
├── config
│   ├── config.yaml
│   ├── README.md
│   └── samples.csv
└── workflow
    ├── envs
    │   ├── damid.yaml
    │   ├── deeptools.yaml
    │   ├── peak_calling.yaml
    │   ├── R.yaml
    │   └── trim.yaml
    ├── report
    │   ├── annotated_peaks.rst
    │   ├── correlation.rst
    │   ├── distance_to_tss.rst
    │   ├── feature_distributions.rst
    │   ├── heatmap.rst
    │   ├── mapping_rates.rst
    │   ├── pca.rst
    │   ├── profile_plot.rst
    │   ├── scree.rst
    │   └── workflow.rst
    ├── rules
    │   ├── bedgraph_processing.smk
    │   ├── bed.smk
    │   ├── damid.smk
    │   ├── deeptools.smk
    │   ├── fastqc.smk
    │   ├── motifs.smk
    │   ├── peak_calling.smk
    │   ├── plotting.smk
    │   ├── resources.smk
    │   └── trimming.smk
    ├── schemas
    │   └── config.schema.yaml
    ├── scripts
    │   ├── annotate_peaks.R
    │   ├── average_bigwig.py
    │   ├── average_wig.py
    │   ├── bowtie2_align_to_plasmid.py
    │   ├── convert_bed2fasta.py
    │   ├── create_annotation_file.R
    │   ├── create_background_fasta.py
    │   ├── create_blacklist.py
    │   ├── damidseq_pipeline.py
    │   ├── filter_overlapping_peaks.py
    │   ├── general_functions.smk
    │   ├── get_resource.sh
    │   ├── mask_fasta.py
    │   ├── peak_annotation_plots.R
    │   ├── plot_mapping_rates.R
    │   ├── plot_PCA.R
    │   ├── quantile_norm_bedgraph.py
    │   ├── resources.py
    │   ├── reverse_log2.py
    │   ├── run_find_peaks.py
    │   └── trim_galore.py
    └── Snakefile

7 directories, 51 files

Alternatively, you can clone the repository in a directory of choice, and copy the config and workflow directories to the desired location:

$ cd /path/to/store/code
$ git clone https://github.com/niekwit/damid-seq.git
$ cp -r damid-seq/config damid-seq/workflow /path/to/analysis

This will download the development version of the workflow.

If you want to obtain a specific release instead:

$ cd /path/to/store/code
$ git clone https://github.com/niekwit/damid-seq.git -b v0.5.0
$ cp -r damid-seq/config damid-seq/workflow /path/to/analysis