https://github.com/cbg-ethz/shm
Deep hierarchical models combined with Markov random fields.
Science Score: 26.0%
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Low similarity (11.0%) to scientific vocabulary
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Repository
Deep hierarchical models combined with Markov random fields.
Basic Info
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Metadata Files
README.md
Structured hierarchical models 
Deep hierarchical programs combined with categorical Markov random fields.
About
Structured hierarchical models are a family of generative models for probabilistic inference of causal effects from genetic perturbation screens. SHMs utilize classical hierarchical models to represent heterogeneous data and combine them with categorical Markov random fields to encode biological prior information over functionally related genes. The random field induces a clustering of the genes which helps to inform inference of parameters in the hierarchical model. SHMs are designed for extremely noisy, experimental data sets for which the true data generating process is difficult to model.
An SHM has the following basic structure.
The top-level categorical variables $zg$ are latent cluster assignments for $g$ genes with effect sizes $\gammag$. The effect sizes are used to parameterize a deep hierarchical model, for instance to represent a heterogeneous data set $y_{gci}$ of multiple conditions $c$ and interventions $i$.
Installation
You can install the package using:
pip install https://github.com/cbg-ethz/shm/archive/<version>.tar.gz
where <version> is the most recent release on GitHub.
Please don't install from the master branch directly.
Citation
If you like this package, please consider citing it:
Dirmeier, S. and Beerenwinkel, N. (2019). Structured hierarchical models for probabilistic inference from perturbation screening data. bioRxiv. https://doi.org/10.1101/848234
Author
Simon Dirmeier simon.dirmeier @ web.de
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
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