https://github.com/bigbio/py-pgatk
Python tools for proteogenomics analysis toolkit
Science Score: 26.0%
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○CITATION.cff file
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✓codemeta.json file
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○.zenodo.json file
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✓DOI references
Found 2 DOI reference(s) in README -
○Academic publication links
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○Scientific vocabulary similarity
Low similarity (15.3%) to scientific vocabulary
Keywords
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Repository
Python tools for proteogenomics analysis toolkit
Basic Info
- Host: GitHub
- Owner: bigbio
- License: apache-2.0
- Language: Python
- Default Branch: master
- Size: 125 MB
Statistics
- Stars: 13
- Watchers: 5
- Forks: 12
- Open Issues: 9
- Releases: 19
Topics
Metadata Files
README.md
ProteoGenomics Analysis Toolkit
pypgatk is a Python library - part of the ProteoGenomics Analysis Toolkit. It provides different bioinformatics tools for proteogenomics data analysis.
Requirements:
The package requirements vary depending on the way that you want to install it (you need one of the following):
- pip: if installation goes through pip, you will require Python3 and pip3 installed.
- Bioconda: if installation goes through Bioconda, you will require that conda is installed and configured to use bioconda channels.
- Docker container: to use pypgatk from its docker container you will need Docker installed.
- Source code: to use and install from the source code directly, you will need to have git, Python3 and pip.
Installation
pip
You can install pypgatk with pip:
pip install pypgatk
Bioconda
You can install pypgatk with bioconda (please setup conda and the bioconda channel if you haven't first, as explained here):
conda install pypgatk
Available as a container
You can use the pypgatk tool already setup on a Docker container. You need to choose from the available tags here and replace it in the call below where it says <tag>.
docker pull quay.io/biocontainers/pypgatk:<tag>
NOTE: Please note that Biocontainers containers do not have a latest tag, as such a docker pull/run without defining the tag will fail. For instance, a valid call would be (for version 0.0.2):
docker run -it quay.io/biocontainers/pypgatk:0.0.2--py_0
Inside the container, you can either use the Python interactive shell or the command line version (see below).
Use latest source code
Alternatively, for the latest version, clone this repo and go into its directory, then execute pip3 install . :
``` git clone https://github.com/bigbio/py-pgatk cd py-pgatk
you might want to create a virtualenv for pypgatk before installing
pip3 install . ```
Usage
The pypgatk design combines multiple modules and tools into one framework. All the possible commands are accessible using the commandline tool pypgatk_cli.py.
The library provides multiple commands to download, translate and generate protein sequence databases from reference and mutation genome databases.
``` $: pypgatk_cli -h
Usage: pypgatk [OPTIONS] COMMAND [ARGS]...
This is the main tool that give access to all commands and options provided by the pypgatk
Options: --version Show the version and exit. -h, --help Show this message and exit.
Commands: cbioportal-downloader Command to download the the cbioportal studies cbioportal-to-proteindb Command to translate cbioportal mutation data into proteindb cosmic-downloader Command to download the cosmic mutation database cosmic-to-proteindb Command to translate Cosmic mutation data into proteindb dnaseq-to-proteindb Generate peptides based on DNA sequences ensembl-check Command to check ensembl database for stop codons, gaps ensembl-downloader Command to download the ensembl information generate-decoy Create decoy protein sequences using multiple methods DecoyPYrat, Reverse/Shuffled Proteins. generate-deeplc Generate input for deepLC tool from idXML,mzTab or consensusXML msrescore-configuration Command to generate the msrescore configuration file from idXML peptide-class-fdr Command to compute the Peptide class FDR threeframe-translation Command to perform 3'frame translation vcf-to-proteindb Generate peptides based on DNA variants VCF files
```
Full Documentation
https://pgatk.readthedocs.io/en/latest/pypgatk.html
Cite as
Husen M Umer, Enrique Audain, Yafeng Zhu, Julianus Pfeuffer, Timo Sachsenberg, Janne Lehtiö, Rui M Branca, Yasset Perez-Riverol Generation of ENSEMBL-based proteogenomics databases boosts the identification of non-canonical peptides Bioinformatics, Volume 38, Issue 5, 1 March 2022, Pages 1470–1472 https://doi.org/10.1093/bioinformatics/btab838
Owner
- Name: BigBio Stack
- Login: bigbio
- Kind: organization
- Email: proteomicsstack@gmail.com
- Location: Cambridge, UK
- Website: http://bigbio.xyz
- Repositories: 24
- Profile: https://github.com/bigbio
Provide big data solutions Bioinformatics
GitHub Events
Total
- Watch event: 3
- Fork event: 1
Last Year
- Watch event: 3
- Fork event: 1
Committers
Last synced: almost 3 years ago
All Time
- Total Commits: 460
- Total Committers: 7
- Avg Commits per committer: 65.714
- Development Distribution Score (DDS): 0.293
Top Committers
| Name | Commits | |
|---|---|---|
| ypriverol | y****l@g****m | 325 |
| husensofteng | h****g@g****m | 117 |
| Yafeng Zhu | y****u@Y****l | 10 |
| Husen M. Umer | h****g@u****m | 4 |
| enriquea | e****n@g****m | 2 |
| dependabot[bot] | 4****]@u****m | 1 |
| Husen M. Umer | u****m@k****l | 1 |
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 44
- Total pull requests: 40
- Average time to close issues: 7 months
- Average time to close pull requests: 16 days
- Total issue authors: 7
- Total pull request authors: 5
- Average comments per issue: 2.32
- Average comments per pull request: 0.6
- Merged pull requests: 35
- Bot issues: 0
- Bot pull requests: 5
Past Year
- Issues: 1
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 1
- Pull request authors: 0
- Average comments per issue: 1.0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- ypriverol (21)
- husensofteng (17)
- enriquea (2)
- mpage21 (1)
- GeorgesBed (1)
- AlirezaShokrollahi (1)
- OmerRonen (1)
Pull Request Authors
- ypriverol (26)
- husensofteng (9)
- DongdongdongW (6)
- dependabot[bot] (6)
- enriquea (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
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Total downloads:
- pypi 104 last-month
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 21
- Total maintainers: 1
pypi.org: pypgatk
Python tools for proteogenomics
- Homepage: http://github.com/bigbio/py-pgatk
- Documentation: https://pypgatk.readthedocs.io/
- License: LICENSE.txt
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Latest release: 0.0.24
published almost 2 years ago
Rankings
Maintainers (1)
Dependencies
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- ratelimit ==2.2.1
- requests ==2.21.0
- simplejson ==3.16.0