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Commit 71ff875

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committedApr 18, 2023
Updated all dependencies, wrappers and actions; adapted to use mamba
1 parent 2b710b5 commit 71ff875

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‎.github/workflows/main.yaml

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steps:
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- uses: actions/checkout@v3
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- name: Lint workflow
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uses: snakemake/snakemake-github-action@v1.23.0
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uses: snakemake/snakemake-github-action@v1.24.0
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with:
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directory: .test
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snakefile: workflow/Snakefile
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uses: actions/checkout@v3
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- name: Test workflow
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uses: snakemake/snakemake-github-action@v1.23.0
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uses: snakemake/snakemake-github-action@v1.24.0
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with:
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directory: .test
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snakefile: workflow/Snakefile
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args: "--use-conda --show-failed-logs --cores 2 --conda-cleanup-pkgs cache --conda-frontend mamba"
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args: "--use-conda --conda-frontend mamba --show-failed-logs --cores 2 --conda-cleanup-pkgs cache --conda-frontend mamba"
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- name: Test report
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uses: snakemake/snakemake-github-action@v1.23.0
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uses: snakemake/snakemake-github-action@v1.24.0
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with:
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directory: .test
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snakefile: workflow/Snakefile

‎README.md

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### Step 1: Obtain a copy of this workflow
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1. Create a new github repository using this workflow [as a template](https://help.github.com/en/articles/creating-a-repository-from-a-template).
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1. Create a new GitHub repository using this workflow [as a template](https://help.github.com/en/articles/creating-a-repository-from-a-template).
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2. [Clone](https://help.github.com/en/articles/cloning-a-repository) the newly created repository to your local system, into the place where you want to perform the data analysis.
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### Step 2: Configure workflow
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### Step 3: Install Snakemake
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Install Snakemake using [conda](https://conda.io/projects/conda/en/latest/user-guide/install/index.html):
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1. Install [conda](https://conda.io/projects/conda/en/latest/user-guide/install/index.html).
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2. Install [mamba](https://github.com/mamba-org/mamba) in conda base and create a snakemake conda environment:
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```bash
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conda install -n base -c conda-forge mamba
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conda create -c bioconda -c conda-forge -n snakemake snakemake
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```
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For installation details, see the [instructions in the Snakemake documentation](https://snakemake.readthedocs.io/en/stable/getting_started/installation.html).
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Test your configuration by performing a dry-run via
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snakemake --use-conda -n
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snakemake --use-conda --conda-frontend mamba -n
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Execute the workflow locally via
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snakemake --use-conda --cores $N
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snakemake --use-conda --conda-frontend mamba --cores $N
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using `$N` cores or run it in a cluster environment via
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snakemake --use-conda --cluster qsub --jobs 100
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snakemake --use-conda --conda-frontend mamba --cluster qsub --jobs 100
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or
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snakemake --use-conda --drmaa --jobs 100
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snakemake --use-conda --conda-frontend mamba --drmaa --jobs 100
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If you not only want to fix the software stack but also the underlying OS, use
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snakemake --use-conda --use-singularity
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snakemake --use-conda --conda-frontend mamba --use-singularity
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in combination with any of the modes above.
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See the [Snakemake documentation](https://snakemake.readthedocs.io/en/stable/executable.html) for further details.

‎start.sh

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conda activate snakemake
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snakemake --use-conda --cores $(nproc) --show-failed-logs --conda-cleanup-pkgs cache -R all
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snakemake --use-conda --conda-frontend mamba --cores $(nproc) --show-failed-logs --conda-cleanup-pkgs cache -R all
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snakemake --report
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‎start_test.sh

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conda activate snakemake
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snakemake --use-conda --cores $(nproc) --directory .test --show-failed-logs --conda-cleanup-pkgs cache -R all
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snakemake --use-conda --conda-frontend mamba --cores $(nproc) --directory .test --show-failed-logs --conda-cleanup-pkgs cache -R all
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snakemake --report --directory .test
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‎workflow/envs/blast.yaml

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- bioconda
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- conda-forge
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dependencies:
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- blast ==2.10.1
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- openssl >=1.0
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- blast ==2.13.0
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- openssl ==3.1.0

‎workflow/envs/cutadapt_se.yaml

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- conda-forge
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- defaults
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dependencies:
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- cutadapt ==2.10
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- cutadapt ==4.3

‎workflow/envs/noderad.yaml

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- xorg-libxi ==1.7.10
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- xorg-libxcursor ==1.2.0
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- xorg-libxdamage ==1.1.5
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- xorg-libxcomposite ==0.4.5
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- xorg-libxcomposite ==0.4.6
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- xorg-libxrandr ==1.5.2
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- xorg-libxinerama ==1.1.4
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- graph-tool ==2.37
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- pysam ==0.16
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- biopython ==1.78
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- xorg-libxinerama ==1.1.5
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- graph-tool ==2.53
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- pysam ==0.21.0
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- biopython ==1.81

‎workflow/envs/plots_blast.yaml

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- bioconda
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- conda-forge
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dependencies:
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- r-tidyverse ==1.3.0
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- r-stringr ==1.4.0
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- r-tidyverse ==2.0.0
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- r-stringr ==1.5.0

‎workflow/envs/sim_to_fasta.yaml

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- bioconda
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- conda-forge
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dependencies:
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- pyyaml ==5.3
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- pyyaml ==6.0

‎workflow/rules/evaluation.smk

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log:
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"logs/evaluation/index/{type}_fasta/{sample}.{type}.fasta"
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wrapper:
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"v0.69.0/bio/samtools/faidx"
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"v1.25.0/bio/samtools/faidx"
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rule blast_database:
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input:

‎workflow/rules/noderad.smk

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"logs/minimap2/{sample}.log"
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threads: 3
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wrapper:
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"0.66.0/bio/minimap2/index"
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"v1.25.0/bio/minimap2/index"
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# determine edit distances and best alignment with minimap2
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rule minimap2:
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extra="-a -A 10 -N 100 --eqx --cs=long"
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threads: 3
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wrapper:
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"0.66.0/bio/minimap2/aligner"
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"v1.25.0/bio/minimap2/aligner"
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# converts SAM files to BAM files
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rule samtools_view:
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params:
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" -b "
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wrapper:
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"v0.69.0/bio/samtools/view"
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"v1.25.0/bio/samtools/view"
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# RADSeq analysis: calulates alleles and loci likelihoods and returns vcf file with with the most probable loci
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rule noderad:

‎workflow/rules/qc.smk

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log:
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"logs/qc/fastqc/{sample}_fastqc.log"
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wrapper:
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"0.66.0/bio/fastqc"
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"v1.25.0/bio/fastqc"
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rule multiqc:
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input:
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log:
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"logs/qc/multiqc.log"
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wrapper:
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"0.66.0/bio/multiqc"
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"v1.25.0/bio/multiqc"

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