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Major changes fixing issues in reading params from configs files
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# Python tools for ProteoGenomics Analysis Toolkit | ||
# ProteoGenomics Analysis Toolkit | ||
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![Python application](https://github.com/bigbio/py-pgatk/workflows/Python%20application/badge.svg) | ||
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[![PyPI version](https://badge.fury.io/py/pypgatk.svg)](https://badge.fury.io/py/pypgatk) | ||
![PyPI - Downloads](https://img.shields.io/pypi/dm/pypgatk) | ||
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**pypgatk** is a Python library part of the [ProteoGenomics Analysis Toolkit](https://pgatk.readthedocs.io/en/latest). It provides different bioinformatics tools for proteogenomics data analysis. | ||
**pypgatk** is a Python library - part of the [ProteoGenomics Analysis Toolkit](https://pgatk.readthedocs.io/en/latest). It provides different bioinformatics tools for proteogenomics data analysis. | ||
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# Requirements: | ||
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This package requirements vary depending on the way that you want to install it (all three are independent, you don't need all these requirements): | ||
The package requirements vary depending on the way that you want to install it (you need one of the following): | ||
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- 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](https://bioconda.github.io/user/index.html). | ||
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The pypgatk design combines multiple modules and tools into one framework. All the possible commands are accessible using the commandline tool `pypgatk_cli.py`. | ||
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The library provides multiple commands to download, translate and generate protein sequence databases from reference and mutation genome databases. | ||
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``` | ||
$: pypgatk_cli.py -h | ||
$: 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-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. Each protein is | ||
reversed and the cleavage sites switched with | ||
preceding amino acid. Peptides are checked for | ||
existence in target sequences if foundthe tool will | ||
attempt to shuffle them. [email protected] | ||
2015 | ||
threeframe-translation Command to perform 3frame translation | ||
vcf-to-proteindb Generate peptides based on DNA variants from | ||
ENSEMBL VEP VCF files | ||
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 | ||
``` | ||
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The library provides multiple commands to download, translate and generate protein sequence databases from reference and mutation genome databases. | ||
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# Full Documentation | ||
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[https://pgatk.readthedocs.io/en/latest/pypgatk.html](https://pgatk.readthedocs.io/en/latest/pypgatk.html) | ||
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## 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 | ||
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 | ||
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