Supporting data for "VariantSpark: A Distributed Implementation of Random Forest Tailored for Ultra High Dimensional Genomic Data"

Many traits and diseases are thought to be driven by more than one gene (polygenic). Polygenic Risk Scores (PRS) hence expand on Genome-Wide Association Studies (GWAS) by taking multiple genes into account when building risk models. However, PRS only considers the additive effect of individual genes...

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Bibliographische Detailangaben

Hauptverfasser:	Arash, Bayat, Szul Piotr, Aidan, O'Brien R., Robert, Dunne, Brendan, Hosking, Yatish, Jain, Cameron, Hosking, Oscar, Luo J., Natalie, Twine, Denis, Bauer C.
Format:	Dataset
Sprache:	eng
Schlagworte:	cloud computing epistasis Genomic gwas machine learning polygenic polygenic risk scores random forest Software ultra-high dimensional
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