Transcriptome prediction performance across machine learning models and diverse ancestries

Transcriptome prediction performance across machine learning models and diverse ancestries

Summary: Transcriptome prediction methods such as PrediXcan and FUSION have become popular in complex trait mapping. Most transcriptome prediction models have been trained in European populations using methods that make parametric linear assumptions like the elastic net (EN). To potentially further...

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Bibliographic Details
Main Authors: Paul C. Okoro, Ryan Schubert, Xiuqing Guo, W. Craig Johnson, Jerome I. Rotter, Ina Hoeschele, Yongmei Liu, Hae Kyung Im, Amy Luke, Lara R. Dugas, Heather E. Wheeler
Format: Article
Language:English
Published: Elsevier 2021-04-01
Series:HGG Advances
Subjects:
gene expression
transcriptome prediction
transcriptome-wide association studies
African ancestries
Hispanic ancestries
European ancestries
Online Access:http://www.sciencedirect.com/science/article/pii/S2666247720300191

Internet

http://www.sciencedirect.com/science/article/pii/S2666247720300191

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