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https://github.com/iwhalen/tblup

Trait BLUP, a Feature Selection Package for Genomic Prediction
https://github.com/iwhalen/tblup

differential-evolution evolutionary-computation feature-selection genomic-prediction

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Trait BLUP, a Feature Selection Package for Genomic Prediction

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# TBLUP

Trait BLUP [1,2], a large scale feature selection for genomic prediction using differential evolution; a fairly simple algorithm that assigns fitness based off an individual's GBLUP [3] accuracy.

See `main.py` for an example of how to run. This implementation uses numpy matrices throughout.
Convert data accordingly.

See `requirements.txt` for dependencies. Use the command `pip3 install -r requirements.txt` to install the required libraries.

See `generate_sbs.py` to generate SLURM sbatch scripts for various experiments.

#### Citations

[1] Esquivelzeta-Rabell, C & Al-Mamun, Hawlader & Lee, Sang-Han & K Lee, H & D Song,
K & Gondro, Cedric. (2015). Evolving to the Best SNP Panel for Hanwoo Breed
Proportion Estimates.

[2] Al-Mamun, Hawlader & Kwan, Paul & Clark, Sam & Lee, Sang-Han & Lee,
H K & Gondro, Cedric. (2015). Genomic Best Linear Unbiased Prediction Using
Differential Evolution.

[3] Clark S.A., van der Werf J. (2013) Genomic Best Linear Unbiased Prediction (gBLUP) for the
Estimation of Genomic Breeding Values. In: Gondro C., van der Werf J., Hayes B. (eds)
Genome-Wide Association Studies and Genomic Prediction. Methods in Molecular Biology (Methods
and Protocols), vol 1019. Humana Press, Totowa, NJ