Science Score: 67.0%
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✓CITATION.cff file
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✓codemeta.json file
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✓DOI references
Found 1 DOI reference(s) in README -
✓Academic publication links
Links to: biorxiv.org -
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○Scientific vocabulary similarity
Low similarity (3.6%) to scientific vocabulary
Last synced: 6 months ago
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Repository
Basic Info
- Host: GitHub
- Owner: Khatri-Lab
- Language: Python
- Default Branch: main
- Size: 4.88 KB
Statistics
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
- Releases: 2
Created over 3 years ago
· Last pushed about 3 years ago
Metadata Files
Readme
Citation
README.md
MIDAS- Model-independent Inference of Directed AssociationS
Code for method described in Ganesan et al., bioRxiv 2022
Problem statement
Given tabular data with n columns, to infer directed associations between pairs of columns
Approach
- Train ML models predicting one column using all other columns in round-robin fashion
- Models are fixed after this point
- Compute R2 for the prediction of each column in test data
- Perturb each input column systematically for a given output column in test data
- Compute R2 using perturbed data
- Compute association strength from input to output as relative difference in true and perturbed R2
Owner
- Name: Khatri-Lab
- Login: Khatri-Lab
- Kind: organization
- Repositories: 2
- Profile: https://github.com/Khatri-Lab
Citation (CITATION.cff)
cff-version: 1.1.0
message: "If you use this software, please cite it as below."
authors:
- family-names: Ganesan
given-names: Ananthakrishnan
title: Khatri-Lab/midas: Ganesan et al., 2022, iScience
version: v1.0
date-released: 2022-12-01