Science Score: 65.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 2 DOI reference(s) in README -
○Academic publication links
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○Academic email domains
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✓Institutional organization owner
Organization hausergroup has institutional domain (drug.ku.dk) -
○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (10.3%) to scientific vocabulary
Repository
Regenie QC and analysis in the UKB Jupyterlab
Basic Info
- Host: GitHub
- Owner: HauserGroup
- License: mit
- Language: Jupyter Notebook
- Default Branch: main
- Size: 8.18 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 7
- Releases: 1
Metadata Files
README.md
gogoGPCR2
Note that much of the code is custom to the project and may not be directly applicable to other projects. Please contact the authors for assistance and collaboration on using this code
gogoGPCR2 is a framework for performing burden testing on UK Biobank Research Analysis Platform (RAP). It can be used as inspiration for burden testing on Whole-Exome Sequencing (WES) and Whole Genome Sequencing (WGS) data in the UKB using regenie. Despite the name, gogoGPCR2 can be used for analyses of any (set of) gene(s)
This repo contains a series of notebooks, for pre-processing and quality controlling phenotype and genetic data, a Dockerfile for pre-processing phenotypes with PHESANT, and a series of scripts, for performing burden testing, with regenie. For information on running individual notebooks and scripts, see notebooks/[WES/WGS]/README.md and scripts/[WES/WGS]/README.md, respectively.
Usage
Notebooks and scripts should be run in numerical order. Notebooks and scripts starting with "0*" should only be run once and the output files can be re-used for further analyses.
Citation
Kizilkaya, H.S., Sørensen, K.V., Madsen, J.S. et al. Characterization of genetic variants of GIPR reveals a contribution of β-arrestin to metabolic phenotypes. Nat Metab 6, 1268–1281 (2024). https://doi.org/10.1038/s42255-024-01061-4
Owner
- Name: Hauser group
- Login: HauserGroup
- Kind: organization
- Location: Denmark
- Website: https://drug.ku.dk/disciplines/translational-pharmacology/pharmacoinformatics/
- Repositories: 3
- Profile: https://github.com/HauserGroup
Citation (citation.cff)
cff-version: 1.2.0
message: "If you use this code or parts hereof, please cite the article as below."
authors:
- family-names: "Sture Madsen"
given-names: "Jakob"
orcid: "https://orcid.org/0000-0002-2841-7284"
- family-names: "Hauser"
given-names: "Alexander"
orcid: "https://orcid.org/0000-0003-1098-6419"
title: "gogoGPCR2"
version: 0.1.0
date-released: 2024-06-13
url: "https://github.com/jsture/gogoGPCR2"
preferred-citation:
type: article
authors:
- family-names: "Kizilkaya"
given-names: "Hüsün"
orcid: "http://orcid.org/0000-0003-2406-9507"
- family-names: "Sørensen"
given-names: "Kimmie"
orcid: "http://orcid.org/0000-0002-3861-4484"
- family-names: "Sture Madsen"
given-names: "Jakob"
orcid: "https://orcid.org/0000-0002-2841-7284"
- family-names: "Hauser"
given-names: "Alexander"
orcid: "https://orcid.org/0000-0003-1098-6419"
doi: "10.1038/s42255-024-01061-4"
url: "https://www.nature.com/articles/s42255-024-01061-4"
journal: "Nature Metabolism"
month: 6
title: "Characterization of genetic variants of GIPR reveals a contribution of β-arrestin to metabolic phenotypes"
year: 2024
GitHub Events
Total
- Issues event: 6
- Delete event: 1
- Issue comment event: 1
- Member event: 3
- Push event: 5
- Pull request event: 2
- Pull request review event: 5
- Pull request review comment event: 2
- Create event: 1
Last Year
- Issues event: 6
- Delete event: 1
- Issue comment event: 1
- Member event: 3
- Push event: 5
- Pull request event: 2
- Pull request review event: 5
- Pull request review comment event: 2
- Create event: 1
Dependencies
- rocker/r-ver 3.3.1 build
- dxdata >=0.0.1
- dxpy >=0.381.0
- hail ==0.2.116
- jupyterlab >=4.2.5
- numpy ==1.23.5
- pandas >=2.2.2
- pre-commit >=3.8.0
- scipy ==1.9.3