Digital Trials pipeline configured for WES
Source-only snapshot of the cluster branch for WES execution. Large reference files (HPA/MANE/ensemble FASTA, model weights, ~597 MB) are omitted: they are baked into the container images at build time and mounted from the dreamdock-data PVC at runtime, and exceed the Gitea request size limit. Pipeline entry point is main.nf, which orchestrates the biotransformer, conplex and tissue modules as a single workflow. Ligand inputs are read from the eureka workspace; protein_zarr and chembl_db come from the dreamdock-data PVC.
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Olamide Isreal
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Dockerfile_conplex
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Dockerfile_conplex
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ARG CUDA=11.7
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FROM nvidia/cuda:${CUDA}.1-cudnn8-devel-ubuntu22.04
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USER root
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SHELL ["/bin/bash", "-c"]
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WORKDIR /home
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RUN mkdir -p /home/omic
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WORKDIR /home/omic
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ARG DEBIAN_FRONTEND=noninteractive
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RUN apt-get update -y && apt-get install -y --no-install-recommends \
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build-essential \
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cmake \
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curl \
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git \
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wget \
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ca-certificates \
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hmmer \
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kalign \
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tzdata \
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&& apt-get clean \
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&& rm -rf /var/lib/apt/lists/*
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# Add the NVIDIA GPG key directly
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RUN wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.0-1_all.deb
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RUN dpkg -i cuda-keyring_1.0-1_all.deb && rm cuda-keyring_1.0-1_all.deb
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RUN apt-get -y update && \
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apt-get install -y --no-install-recommends cuda-command-line-tools-11-7
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RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh \
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&& bash miniconda.sh -b -p /opt/conda \
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&& rm miniconda.sh \
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&& ln -s /opt/conda/etc/profile.d/conda.sh /etc/profile.d/conda.sh \
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&& echo ". /opt/conda/etc/profile.d/conda.sh" >> ~/.bashrc \
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&& echo "conda activate base" >> ~/.bashrc \
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&& find /opt/conda/ -follow -type f -name '*.a' -delete \
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&& find /opt/conda/ -follow -type f -name '*.js.map' -delete \
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&& /opt/conda/bin/conda clean -afy
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ENV PATH /opt/conda/bin:$PATH
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RUN conda update -y -n base -c defaults conda
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# main conda env (conplex)
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RUN conda create -n conplex-dti python=3.9
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ENV PATH "$PATH:/opt/conda/envs/conplex-dti/bin"
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RUN echo "source activate conplex-dti" >> ~/.bashrc
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RUN conda clean --all -f -y
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# main conda env (secse)
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#RUN conda create --name secse -c conda-forge parallel tqdm biopandas openbabel chemprop xlrd=2 pandarallel python=3.9 perl=5.32
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#RUN conda install -y -n secse -c conda-forge pandas=1.3.5
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#RUN conda install -y -n secse -c conda-forge rdkit=2022.03.5
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#RUN echo "conda activate secse" >> ~/.bashrc
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#ENV PATH="$PATH:/opt/conda/envs/secse/bin"
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#ARG PATH="$PATH:/opt/conda/envs/secse/bin"
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RUN git clone https://github.com/samsledje/ConPLex.git
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WORKDIR /home/omic/ConPLex
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# Install conplex
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RUN apt-get -y update && apt-get install -y ca-certificates && update-ca-certificates
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RUN /opt/conda/envs/conplex-dti/bin/python3 -m pip install conplex-dti
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RUN conplex-dti --help
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# Package into python script for running in nextflow
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COPY conplex.py /home/omic/ConPLex/conplex.py
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RUN chmod +x /home/omic/ConPLex/conplex.py
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# Install pretrained models
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RUN mkdir -p /home/omic/ConPLex/models
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RUN wget --no-check-certificate -O /home/omic/ConPLex/models/ConPLex_v1_BindingDB.pt https://cb.csail.mit.edu/cb/conplex/data/models/BindingDB_ExperimentalValidModel.pt
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# Test
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RUN conplex-dti predict --data-file /home/omic/ConPLex/tests/toy_predict.tsv --model-path /home/omic/ConPLex/models/ConPLex_v1_BindingDB.pt --outfile ./results.tsv
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#copy protein reference trascipt fasta file
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COPY ensemble_reference.fasta .
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COPY MANE_referent_transcipt_reference.fasta .
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COPY MANE_all_transcipts.csv .
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COPY get_round_2.py .
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RUN chmod +x /home/omic/ConPLex/get_round_2.py
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#new model weights
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COPY Run_best_model_epoch46.pt /home/omic/ConPLex/models/
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# Fix predict.py not working on single protein-ligand complex
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#COPY predict.py /home/omic/ConPLex/conplex_dti/cli/predict.py
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#COPY predict.py /opt/conda/envs/conplex-dti/lib/python3.9/site-packages/conplex_dti/cli/predict.py
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#RUN chmod +x /home/omic/ConPLex/conplex_dti/cli/predict.py
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#RUN chmod +x /opt/conda/envs/conplex-dti/lib/python3.9/site-packages/conplex_dti/cli/predict.py
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# Clone secse
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#RUN git clone https://github.com/KeenThera/SECSE.git
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#RUN mv /home/omic/ConPLex/SECSE/secse /home/omic/ConPLex/secse && rm -r /home/omic/ConPLex/SECSE && rm -r /home/omic/ConPLex/secse/scoring
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#COPY secse/scoring /home/omic/ConPLex/secse/scoring
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#COPY secse/grow_processes.py /home/omic/ConPLex/secse/scoring/grow_processes.py
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#RUN chmod +x /home/omic/ConPLex/secse/grow_processes.py
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#RUN chmod +x /home/omic/ConPLex/secse/scoring/ranking.py
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#RUN chmod +x /home/omic/ConPLex/secse/growing/mutation/mutation.py
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# Add missing boost
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#RUN conda install -n secse -c conda-forge boost
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# Install CREM for chemical growth
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#RUN git clone https://github.com/DrrDom/crem.git
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#RUN /opt/conda/envs/conplex-dti/bin/python3 -m pip install crem pandas numpy
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#WORKDIR /home/omic/ConPLex
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#RUN chmod -R +x /home/omic/ConPLex
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#ENV PATH="$PATH:/opt/conda/envs/secse/bin:/home/omic/ConPLex/secse"
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#ENV SECSE="/home/omic/ConPLex/secse"
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#ENV PYTHONPATH="PYTHONPATH=/home/omic/ConPLex/secse:/home/omic/ConPLex:/home/omic/ConPLex/crem"
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#ARG PYTHONPATH="PYTHONPATH=/home/omic/ConPLex/secse:/home/omic/ConPLex:/home/omic/ConPLex/crem"
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# Package into python script for running in nextflow
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#COPY conplex.py /home/omic/ConPLex/conplex.py
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#RUN chmod +x /home/omic/ConPLex/conplex.py
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#Mutation file
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#RUN /opt/conda/envs/conplex-dti/bin/python3 -m pip install crem
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#RUN wget https://www.dropbox.com/s/4r48ohopechsd59/replacements02_sa2.db.gz?dl=0
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#RUN mv replacements02_sa2.db.gz?dl=0 replacements02_sa2.db.gz
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#RUN gzip -d replacements02_sa2.db.gz
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#COPY fragment_mutations.py /home/omic/ConPLex/fragment_mutations.py
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#RUN chmod +x /home/omic/ConPLex/fragment_mutations.py
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