Structure_threader
causal-learn
| Structure_threader | causal-learn | |
|---|---|---|
| 1 | 1 | |
| 24 | 988 | |
| - | 3.4% | |
| 3.3 | 7.9 | |
| 9 months ago | 21 days ago | |
| Python | Python | |
| GNU General Public License v3.0 only | MIT License |
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Structure_threader
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Two ways to parallelize STRUCTURE
There is also structure_threader which works amazingly for me (Github Link)
causal-learn
What are some alternatives?
directory-structure - :package: Print a directory tree structure in your Python code.
dowhy - DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
OSGenome - An Open Source Web Application for Genetic Data (SNPs) using 23AndMe and Data Crawling Technologies
dodiscover - [Experimental] Global causal discovery algorithms
tfcausalimpact - Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.
sections - Easy Python tree data structures
looper - A resource list for causality in statistics, data science and physics
HumesGuillotine - Hume's Guillotine: Beheading the social pseudo-sciences with the Algorithmic Information Criterion for CAUSAL model selection.
genome_integration - MR-link and genome integration. genome_integration is a repository for the analysis of genomic data. Specifically, the repository implements the causal inference method MR-link, as well as other Mendelian randomization methods.