MEDIPIPE | automatically deploy the execution environments
kandi X-RAY | MEDIPIPE Summary
kandi X-RAY | MEDIPIPE Summary
MEDIPIPE is a HTML library. MEDIPIPE has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.
MEDIPIPE
MEDIPIPE
Support
Quality
Security
License
Reuse
Support
MEDIPIPE has a low active ecosystem.
It has 6 star(s) with 0 fork(s). There are 2 watchers for this library.
It had no major release in the last 6 months.
There are 1 open issues and 0 have been closed. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of MEDIPIPE is v1.0.0-beta
Quality
MEDIPIPE has no bugs reported.
Security
MEDIPIPE has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
MEDIPIPE is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
Reuse
MEDIPIPE releases are not available. You will need to build from source code and install.
Installation instructions, examples and code snippets are available.
Top functions reviewed by kandi - BETA
kandi's functional review helps you automatically verify the functionalities of the libraries and avoid rework.
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of MEDIPIPE
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of MEDIPIPE
MEDIPIPE Key Features
No Key Features are available at this moment for MEDIPIPE.
MEDIPIPE Examples and Code Snippets
No Code Snippets are available at this moment for MEDIPIPE.
Community Discussions
No Community Discussions are available at this moment for MEDIPIPE.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install MEDIPIPE
Make sure that you have a Conda-based Python3 distribution(e.g.,the Miniconda). The Miniconda3-py38_23.3.1-0-Linux-x86_64.sh for Linux is prefered to avoid potential cnflicts. The installation of Mamba is also recommended:. Git clone this pipeline. Install pipeline's core enviroment. IMPORTANT: EXTRA ENVIRONMENTS WILL BE INSTALLED, MAKE SURE YOU STILL HAVE INTERNET ACCESS.
Make sure that you have a Conda-based Python3 distribution(e.g.,the Miniconda). The Miniconda3-py38_23.3.1-0-Linux-x86_64.sh for Linux is prefered to avoid potential cnflicts. The installation of Mamba is also recommended: $ conda install -n base -c conda-forge mamba
Git clone this pipeline. $ cd $ git clone https://github.com/yzeng-lol/MEDIPIPE
Install pipeline's core enviroment $ cd MEDIPIPE $ conda activate base $ mamba env create --file conda_env.yaml
Test run IMPORTANT: EXTRA ENVIRONMENTS WILL BE INSTALLED, MAKE SURE YOU STILL HAVE INTERNET ACCESS. Step 1: Prepare reference, samples FASTQ and aggregation files according to templates. Step 2: Specify input configuration file by following the instructions here. NOTE: For testing run, you can simply run the SED command below to specify files in Step1,2.The toy dataset will fail to fit sigmoid model for MEDStrand due to low read depth, but you can still find other results in ./test/Res. $ sed -i 's,/path/to,'"$PWD"',g' ./test/*template.* $ conda activate MEDIPIPE $ snakemake --snakefile ./workflow/Snakefile \ --configfile ./test/config_template.yaml \ --conda-prefix ${CONDA_PREFIX}_extra_env \ --use-conda --cores 4 -p
Run on HPCs You can also submit this pipeline to clusters with the template ./workflow/sbatch_Snakefile_template.sh. This template is for SLURM, however, it could be modified to different resource management systems. More details about cluster configuration can be found at here. ## Test run by SLURM submission $ sed -i 's,/path/to,'"$PWD"',g' ./workflow/sbatch_Snakefile_template.sh # replace PATHs for testing $ sbatch ./workflow/sbatch_Snakefile_template.sh
Make sure that you have a Conda-based Python3 distribution(e.g.,the Miniconda). The Miniconda3-py38_23.3.1-0-Linux-x86_64.sh for Linux is prefered to avoid potential cnflicts. The installation of Mamba is also recommended: $ conda install -n base -c conda-forge mamba
Git clone this pipeline. $ cd $ git clone https://github.com/yzeng-lol/MEDIPIPE
Install pipeline's core enviroment $ cd MEDIPIPE $ conda activate base $ mamba env create --file conda_env.yaml
Test run IMPORTANT: EXTRA ENVIRONMENTS WILL BE INSTALLED, MAKE SURE YOU STILL HAVE INTERNET ACCESS. Step 1: Prepare reference, samples FASTQ and aggregation files according to templates. Step 2: Specify input configuration file by following the instructions here. NOTE: For testing run, you can simply run the SED command below to specify files in Step1,2.The toy dataset will fail to fit sigmoid model for MEDStrand due to low read depth, but you can still find other results in ./test/Res. $ sed -i 's,/path/to,'"$PWD"',g' ./test/*template.* $ conda activate MEDIPIPE $ snakemake --snakefile ./workflow/Snakefile \ --configfile ./test/config_template.yaml \ --conda-prefix ${CONDA_PREFIX}_extra_env \ --use-conda --cores 4 -p
Run on HPCs You can also submit this pipeline to clusters with the template ./workflow/sbatch_Snakefile_template.sh. This template is for SLURM, however, it could be modified to different resource management systems. More details about cluster configuration can be found at here. ## Test run by SLURM submission $ sed -i 's,/path/to,'"$PWD"',g' ./workflow/sbatch_Snakefile_template.sh # replace PATHs for testing $ sbatch ./workflow/sbatch_Snakefile_template.sh
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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