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Submitting Author: Name (@github_handle)
Package Name: gentropy
One-Line Description of Package: Open Targets python framework for post-GWAS analysis
Repository Link (if existing): https://github.com/opentargets/gentropy
Code of Conduct & Commitment to Maintain Package
I agree to abide by pyOpenSci's Code of Conduct during the review process and in maintaining my package after should it be accepted.
Open Targets Gentropy is a Python package to facilitate the interpretation and analysis of GWAS and functional genomic studies for target identification. This package contains a toolkit for the harmonisation, statistical analysis and prioritisation of genetic signals to assist drug discovery.
Community Partnerships
We partner with communities to support peer review with an additional layer of
checks that satisfy community requirements. If your package fits into an
existing community please check below:
Please indicate which category or categories this package falls under:
Data processing and munging
Scope
Please indicate which category or categories.
Check out our package scope page to learn more about our
scope. (If you are unsure of which category you fit, we suggest you make a pre-submission inquiry):
Data retrieval
Data extraction
Data processing/munging
Data deposition
Data validation and testing
Data visualization
Workflow automation
Citation management and bibliometrics
Scientific software wrappers
Database interoperability
Domain Specific
Geospatial
Education
Community Partnerships
If your package is associated with an
existing community please check below:
Explain how and why the package falls under these categories (briefly, 1-2 sentences). Please note any areas you are unsure of:
Gentropy package allows for retrieval of GWAS genomics data with provided airflow automation from locations like GWAS catalog, GnomAD, Finngen, etc. Whole list of available datasets is present in the datasources
Gentropy also allows for data extraction and processing, as main functionality - step functions provided in the steps allow for conducting Genome wide association studies analysis (GWAS).
Who is the target audience and what are the scientific applications of this package?
Target audience are scientists, labs and biotech industry companies, who want to perform GWAS analysis themselves.
Are there other Python packages that accomplish similar things? If so, how does yours differ? vcf2gwas - this is the workflow for the typical GWAS analysis pandasgwas - this is the package to retrieve GWAS data from GWAS catalog
possibly others minor packages and tools for specific GWAS steps
Any other questions or issues we should be aware of:
This is the project maintained by Open Targets
P.S. Have feedback/comments about our review process? Leave a comment here
The text was updated successfully, but these errors were encountered:
Hello @project-defiant, welcome to pyOpenSci! Sorry it took me so long to get back to you. gentropy is definitely in scope for us, would you mind opening a new submission issue referencing this presubmission enquiry? Thank you.
Hello @project-defiant: I'm going to close this presubmission to avoid rechecks from the Editors in Chief.
Feel free to open your submission issue for gentropy when ready!
Thanks!
Submitting Author: Name (@github_handle)
Package Name: gentropy
One-Line Description of Package: Open Targets python framework for post-GWAS analysis
Repository Link (if existing): https://github.com/opentargets/gentropy
Code of Conduct & Commitment to Maintain Package
Description
Open Targets Gentropy is a Python package to facilitate the interpretation and analysis of GWAS and functional genomic studies for target identification. This package contains a toolkit for the harmonisation, statistical analysis and prioritisation of genetic signals to assist drug discovery.
Community Partnerships
We partner with communities to support peer review with an additional layer of
checks that satisfy community requirements. If your package fits into an
existing community please check below:
Scope
Data processing and munging
Scope
Please indicate which category or categories.
Check out our package scope page to learn more about our
scope. (If you are unsure of which category you fit, we suggest you make a pre-submission inquiry):
Domain Specific
Community Partnerships
If your package is associated with an
existing community please check below:
Astropy:My package adheres to Astropy community standards
Pangeo: My package adheres to the Pangeo standards listed in the pyOpenSci peer review guidebook
Explain how and why the package falls under these categories (briefly, 1-2 sentences). Please note any areas you are unsure of:
Gentropy package allows for retrieval of GWAS genomics data with provided airflow automation from locations like GWAS catalog, GnomAD, Finngen, etc. Whole list of available datasets is present in the datasources
Gentropy also allows for data extraction and processing, as main functionality - step functions provided in the steps allow for conducting Genome wide association studies analysis (GWAS).
Gentropy wraps methods from R coloc package, CARMA and others - each of concrete methods
Who is the target audience and what are the scientific applications of this package?
Target audience are scientists, labs and biotech industry companies, who want to perform GWAS analysis themselves.
Are there other Python packages that accomplish similar things? If so, how does yours differ?
vcf2gwas - this is the workflow for the typical GWAS analysis
pandasgwas - this is the package to retrieve GWAS data from GWAS catalog
possibly others minor packages and tools for specific GWAS steps
This is the project maintained by Open Targets
P.S. Have feedback/comments about our review process? Leave a comment here
The text was updated successfully, but these errors were encountered: