snakemake-workflows/dna-seq-short-read-circle-map
A snakemake workflow for calling extrachromosomal circular DNA in Illumina short-read sequencing data with Circle-Map
Overview
Topics:
Latest release: v1.3.0, Last update: 2024-04-23
Linting: linting: passed, Formatting:formatting: passed
Deployment
Step 1: Install Snakemake and Snakedeploy
Snakemake and Snakedeploy are best installed via the Mamba package manager (a drop-in replacement for conda). If you have neither Conda nor Mamba, it is recommended to install Miniforge. More details regarding Mamba can be found here.
When using Mamba, run
mamba create -c conda-forge -c bioconda --name snakemake snakemake snakedeploy
to install both Snakemake and Snakedeploy in an isolated environment. For all following commands ensure that this environment is activated via
conda activate snakemake
Step 2: Deploy workflow
With Snakemake and Snakedeploy installed, the workflow can be deployed as follows. First, create an appropriate project working directory on your system and enter it:
mkdir -p path/to/project-workdir
cd path/to/project-workdir
In all following steps, we will assume that you are inside of that directory. Then run
snakedeploy deploy-workflow https://github.com/snakemake-workflows/dna-seq-short-read-circle-map . --tag v1.3.0
Snakedeploy will create two folders, workflow
and config
. The former contains the deployment of the chosen workflow as a Snakemake module, the latter contains configuration files which will be modified in the next step in order to configure the workflow to your needs.
Step 3: Configure workflow
To configure the workflow, adapt config/config.yml
to your needs following the instructions below.
Step 4: Run workflow
The deployment method is controlled using the --software-deployment-method
(short --sdm
) argument.
To run the workflow with automatic deployment of all required software via conda
/mamba
, use
snakemake --cores all --sdm conda
Snakemake will automatically detect the main Snakefile
in the workflow
subfolder and execute the workflow module that has been defined by the deployment in step 2.
For further options such as cluster and cloud execution, see the docs.
Step 5: Generate report
After finalizing your data analysis, you can automatically generate an interactive visual HTML report for inspection of results together with parameters and code inside of the browser using
snakemake --report report.zip
Configuration
The following section is imported from the workflow’s config/README.md
.
Describe how to configure the workflow (using config.yaml and maybe additional files). All of them need to be present with example entries inside of the config folder.
To configure this workflow, modify config/config.yaml
according to your needs, following the explanations provided in the file.
Add samples to the TSV
file specified via the samples:
directive in config/config.yaml
.
For each sample, the columns sample_name
, alias
, platform
, and group
have to be defined.
- Samples within the same
group
will be handled jointly. This can for example be multiple samples from the same individual. -
alias
es represent the name of the sample within its group (they can be the same as the sample name, or something simpler / more abstract, liketumor
ornormal
). - The
platform
column needs to contain the used sequencing plaform (with this workflow focused onCircle-Map
, this will always be 'ILLUMINA', for now -- but we keep this info for compatibility with other workflows).
Missing values can be specified by empty columns or by writing NA
. Lines can be commented out with #
.
For each sample, add one or more sequencing units (runs, lanes or replicates) to the TSV
file specified via the units:
directive in config/config.yaml
.
For each unit, the columns unit_name
, sample_name
, fq1
, and fq2
have to be defined.
- Each unit has a
unit_name
, which can be for example be a running number, or an actual run, lane or replicate id. - Each unit has a
sample_name
, which associates it with the biological sample it comes from. - For each unit, define the two paired FASTQ files (columns
fq1
,fq2
, these can point to anywhere on your system). - Optional: Define adapters in the
adapters
column, by putting cutadapt arguments in quotation marks (e.g."-a ACGCGATCG -A GCTAGCGTACT"
). If adapters have already been removed in your raw data, or if you don't want to remove them, just leave this column empty for the respective units.
Missing values can be specified by empty columns or by writing NA
. Lines can be commented out with #
.
Linting and formatting
Linting results
None
Formatting results
None