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Dockerfile
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FROM condaforge/mambaforge:latest
LABEL io.github.snakemake.containerized="true"
LABEL io.github.snakemake.conda_env_hash="e5f6ff0e9e827d0d6bf8717bb46f3394c2356786ca7cde04716f3dd7488a0a45"
RUN apt-get update && apt-get install -y curl
# Step 1: Retrieve conda environments
# Conda environment:
# source: workflow/envs/biopython.yaml
# prefix: /conda-envs/80434b30d852d88ac0d9f0dc4712fcc8
# channels:
# - conda-forge
# - bioconda
# dependencies:
# - python==3.10
# - biopython==1.81
# - pandas==2.0.3
# - pip==23.2.1
# - mafft==7.520
# - gb2seq==0.2.20 (pip)
RUN mkdir -p /conda-envs/80434b30d852d88ac0d9f0dc4712fcc8
COPY workflow/envs/biopython.yaml /conda-envs/80434b30d852d88ac0d9f0dc4712fcc8/environment.yaml
COPY workflow/envs/biopython.post-deploy.sh /conda-envs/80434b30d852d88ac0d9f0dc4712fcc8/post-deploy.sh
# Conda environment:
# source: workflow/envs/fetch.yaml
# prefix: /conda-envs/446520408112f3597796f452c95a7517
# channels:
# - bioconda
# - conda-forge
# dependencies:
# - entrez-direct==16.2
RUN mkdir -p /conda-envs/446520408112f3597796f452c95a7517
COPY workflow/envs/fetch.yaml /conda-envs/446520408112f3597796f452c95a7517/environment.yaml
# Conda environment:
# source: workflow/envs/freyja.yaml
# prefix: /conda-envs/ee7a2e1b4ec9a7a9999f34dddaea0605
# channels:
# - conda-forge
# - bioconda
# dependencies:
# - freyja==1.4.2
RUN mkdir -p /conda-envs/ee7a2e1b4ec9a7a9999f34dddaea0605
COPY workflow/envs/freyja.yaml /conda-envs/ee7a2e1b4ec9a7a9999f34dddaea0605/environment.yaml
# Conda environment:
# source: workflow/envs/gisaidr.yaml
# prefix: /conda-envs/da7a255722228900ab1eeedd1878e1c7
# channels:
# - conda-forge
# dependencies:
# - r-base=4.1.3
# - r-tidyverse==2.0.0
# - r-devtools==2.4.5
# - r-logger==0.2.2
# - Wytamma/GISAIDR (R)
# - curl (R)
RUN mkdir -p /conda-envs/da7a255722228900ab1eeedd1878e1c7
COPY workflow/envs/gisaidr.yaml /conda-envs/da7a255722228900ab1eeedd1878e1c7/environment.yaml
COPY workflow/envs/gisaidr.post-deploy.sh /conda-envs/da7a255722228900ab1eeedd1878e1c7/post-deploy.sh
# Conda environment:
# source: workflow/envs/iqtree.yaml
# prefix: /conda-envs/0a608afb24723cb6fa8aef748f5efbc8
# channels:
# - bioconda
# - conda-forge
# dependencies:
# - iqtree==2.2.2.3
RUN mkdir -p /conda-envs/0a608afb24723cb6fa8aef748f5efbc8
COPY workflow/envs/iqtree.yaml /conda-envs/0a608afb24723cb6fa8aef748f5efbc8/environment.yaml
# Conda environment:
# source: workflow/envs/nextalign.yaml
# prefix: /conda-envs/04a3347f94ddf7e21c34bc49e5246076
# channels:
# - bioconda
# - conda-forge
# dependencies:
# - nextalign==2.13
RUN mkdir -p /conda-envs/04a3347f94ddf7e21c34bc49e5246076
COPY workflow/envs/nextalign.yaml /conda-envs/04a3347f94ddf7e21c34bc49e5246076/environment.yaml
# Conda environment:
# source: workflow/envs/pangolin.yaml
# prefix: /conda-envs/efc6ee175cf0def0e180f8f2f7dd529d
# channels:
# - conda-forge
# - bioconda
# dependencies:
# - pangolin==4.3
RUN mkdir -p /conda-envs/efc6ee175cf0def0e180f8f2f7dd529d
COPY workflow/envs/pangolin.yaml /conda-envs/efc6ee175cf0def0e180f8f2f7dd529d/environment.yaml
# Conda environment:
# source: workflow/envs/quarto_render.yaml
# prefix: /conda-envs/f2a098519cf1f8c4cecb3c13f8c92883
# channels:
# - conda-forge
# - bioconda
# dependencies:
# - r-base==4.3.1
# - r-gt==0.9.0
# - quarto==1.3.450
# - r-jsonlite==1.8.5
# - r-tidyverse==2.0.0
# - r-quarto==1.2
# - r-heatmaply==1.4.2
# - r-readr==2.1.4
RUN mkdir -p /conda-envs/f2a098519cf1f8c4cecb3c13f8c92883
COPY workflow/envs/quarto_render.yaml /conda-envs/f2a098519cf1f8c4cecb3c13f8c92883/environment.yaml
# Conda environment:
# source: workflow/envs/renv.yaml
# prefix: /conda-envs/4b57bfc237ddc217c1f0b04d34dc06ef
# channels:
# - conda-forge
# - bioconda
# dependencies:
# - r-base=4.1.3
# - r-tidyverse==2.0.0
# - r-ggrepel==0.9.3
# - r-stringi==1.7.12
# - r-ggpubr==0.6.0
# - bioconductor-ggtree==3.2.0
# - r-ape==5.7
# - r-adephylo==1.1_13
# - r-pegas==1.2
# - r-data.table==1.14.8
# - r-future.apply==1.11.0
# - r-scales==1.2.1
# - r-showtext==0.9_6
# - r-jsonlite==1.8.5
# - r-logger==0.2.2
RUN mkdir -p /conda-envs/4b57bfc237ddc217c1f0b04d34dc06ef
COPY workflow/envs/renv.yaml /conda-envs/4b57bfc237ddc217c1f0b04d34dc06ef/environment.yaml
# Conda environment:
# source: workflow/envs/snpeff.yaml
# prefix: /conda-envs/1934df0e4df02a7ee33c52f53f9e3c30
# channels:
# - bioconda
# dependencies:
# - snpeff==5.1d
RUN mkdir -p /conda-envs/1934df0e4df02a7ee33c52f53f9e3c30
COPY workflow/envs/snpeff.yaml /conda-envs/1934df0e4df02a7ee33c52f53f9e3c30/environment.yaml
# Conda environment:
# source: workflow/envs/var_calling.yaml
# prefix: /conda-envs/5150d0f0a91d7f7a789a06f453d63479
# channels:
# - conda-forge
# - bioconda
# dependencies:
# - ivar==1.4.2
# - samtools==1.17
RUN mkdir -p /conda-envs/5150d0f0a91d7f7a789a06f453d63479
COPY workflow/envs/var_calling.yaml /conda-envs/5150d0f0a91d7f7a789a06f453d63479/environment.yaml
# Step 2: Generate conda environments
RUN mamba env create --prefix /conda-envs/80434b30d852d88ac0d9f0dc4712fcc8 --file /conda-envs/80434b30d852d88ac0d9f0dc4712fcc8/environment.yaml && \
mamba env create --prefix /conda-envs/446520408112f3597796f452c95a7517 --file /conda-envs/446520408112f3597796f452c95a7517/environment.yaml && \
mamba env create --prefix /conda-envs/ee7a2e1b4ec9a7a9999f34dddaea0605 --file /conda-envs/ee7a2e1b4ec9a7a9999f34dddaea0605/environment.yaml && \
mamba env create --prefix /conda-envs/da7a255722228900ab1eeedd1878e1c7 --file /conda-envs/da7a255722228900ab1eeedd1878e1c7/environment.yaml && \
mamba env create --prefix /conda-envs/0a608afb24723cb6fa8aef748f5efbc8 --file /conda-envs/0a608afb24723cb6fa8aef748f5efbc8/environment.yaml && \
mamba env create --prefix /conda-envs/04a3347f94ddf7e21c34bc49e5246076 --file /conda-envs/04a3347f94ddf7e21c34bc49e5246076/environment.yaml && \
mamba env create --prefix /conda-envs/efc6ee175cf0def0e180f8f2f7dd529d --file /conda-envs/efc6ee175cf0def0e180f8f2f7dd529d/environment.yaml && \
mamba env create --prefix /conda-envs/f2a098519cf1f8c4cecb3c13f8c92883 --file /conda-envs/f2a098519cf1f8c4cecb3c13f8c92883/environment.yaml && \
mamba env create --prefix /conda-envs/4b57bfc237ddc217c1f0b04d34dc06ef --file /conda-envs/4b57bfc237ddc217c1f0b04d34dc06ef/environment.yaml && \
mamba env create --prefix /conda-envs/1934df0e4df02a7ee33c52f53f9e3c30 --file /conda-envs/1934df0e4df02a7ee33c52f53f9e3c30/environment.yaml && \
mamba env create --prefix /conda-envs/5150d0f0a91d7f7a789a06f453d63479 --file /conda-envs/5150d0f0a91d7f7a789a06f453d63479/environment.yaml && \
mamba clean --all -y
# Step 3: Run post-deploy scripts
RUN conda init && . /root/.bashrc && \
conda activate /conda-envs/80434b30d852d88ac0d9f0dc4712fcc8 && \
bash /conda-envs/80434b30d852d88ac0d9f0dc4712fcc8/post-deploy.sh && \
conda activate /conda-envs/da7a255722228900ab1eeedd1878e1c7 && \
bash /conda-envs/da7a255722228900ab1eeedd1878e1c7/post-deploy.sh && \
conda deactivate && \
mamba clean --all -y