https://github.com/cbg-ethz/myeloid-clustering
This repository contains supplementary information, data and code for the manuscript: Bayer et al. 2023, "Network-based clustering unveils interconnected landscapes of genomic and clinical features across myeloid malignancies"
Science Score: 13.0%
This score indicates how likely this project is to be science-related based on various indicators:
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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 -
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○Scientific vocabulary similarity
Low similarity (12.6%) to scientific vocabulary
Keywords
Repository
This repository contains supplementary information, data and code for the manuscript: Bayer et al. 2023, "Network-based clustering unveils interconnected landscapes of genomic and clinical features across myeloid malignancies"
Basic Info
- Host: GitHub
- Owner: cbg-ethz
- License: gpl-3.0
- Language: R
- Default Branch: main
- Homepage: https://myeloid-prediction.ethz.ch/
- Size: 109 MB
Statistics
- Stars: 1
- Watchers: 4
- Forks: 0
- Open Issues: 0
- Releases: 0
Topics
Metadata Files
README.md
Network-Based Clustering Unveils Interconnected Landscapes of Genomic and Clinical Features Across Myeloid Malignancies
This repository provides supplementary information, data, and code associated with the manuscript:
Bayer et al. 2023, "Network-based clustering unveils interconnected landscapes of genomic and clinical features across myeloid malignancies"
https://doi.org/10.1101/2023.10.25.563992
Online Tool
We have also developed an online tool for the classification of new patients across myeloid malignancies. Access it here:
Myeloid Malignancies Prediction Tool
Software
The software is available as an R package, which is hosted on CRAN. For more information on how to use this software, including installation, system requirements and application, please refer to our detailed documentation. - CRAN Package: Software Package - Installation and Example: Code Demo - Documentation: Software Documentation (PDF)
Reproducibility
The numerical simulations can be reproduced via the numerical_simulations folder. The results on the public TCGA datasets can be reproduced by running the files in the tcga_analysis folder. Given the full set of MDA data, all results and figures of the pan-myeloid analysis can be reproduced by running the files provied in the analysis folder. The cluster results from the pan-myeloid clustering analysis can be reproduced by running the code provided in the euler_cluster folder.
License
GNU GPL (see LICENSE file for more details)
Owner
- Name: Computational Biology Group (CBG)
- Login: cbg-ethz
- Kind: organization
- Location: Basel, Switzerland
- Website: https://www.bsse.ethz.ch/cbg
- Twitter: cbg_ethz
- Repositories: 91
- Profile: https://github.com/cbg-ethz
Beerenwinkel Lab at ETH Zurich
GitHub Events
Total
- Watch event: 4
- Push event: 1
Last Year
- Watch event: 4
- Push event: 1
Committers
Last synced: about 2 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| Fritz Bayer | f****r@y****m | 11 |
Committer Domains (Top 20 + Academic)
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Last synced: 12 months ago
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