A Python API for estimating statistical high-order epistasis in genotype-phenotype maps.
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Updated
Aug 18, 2023 - Python
A Python API for estimating statistical high-order epistasis in genotype-phenotype maps.
A package for detecting epistasis by machine learning
Code and simulations using interaction-LD score regression
A tool to predict missing data in sparsely sampled genotype-phenotype maps
Learning the language of phylogeny with MSA Transformer
Inference of Epistatic Gene Networks
PAGER is an efficient genotype encoding strategy designed to improve the detection of non-additive genetic variation in complex trait association studies. PAGER dynamically encodes genetic variants by normalizing mean phenotypic differences between genotype classes.
A Python tool to calculate penetrance tables for high-order epistasis models
PAGER is an efficient genotype encoding strategy designed to improve the detection of non-additive genetic variation in complex trait association studies. PAGER dynamically encodes genetic variants by normalizing mean phenotypic differences between genotype classes.
Complete reproduction of 'Generation-Updated Orthogonal Epistatic Kernels for Cross-Generation Genomic Prediction' - NOIA encoding, multi-kernel AI-REML, forward simulation, ablation study. 137 tests, 100% coverage.
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