Leveraging pleiotropic association using sparse group variable selection in genomics data

Leveraging pleiotropic association using sparse group variable selection in genomics data

Abstract Background Genome-wide association studies (GWAS) have identified genetic variants associated with multiple complex diseases. We can leverage this phenomenon, known as pleiotropy, to integrate multiple data sources in a joint analysis. Often integrating additional information such as gene p...

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Bibliographic Details
Main Authors: Matthew Sutton, Pierre-Emmanuel Sugier, Therese Truong, Benoit Liquet
Format: Article
Language:English
Published: BMC 2022-01-01
Series:BMC Medical Research Methodology
Subjects:
Genetic epidemiology
High dimensional data
Lasso penalization
Oncology
Pathway analysis
Pleiotropy
Online Access:https://doi.org/10.1186/s12874-021-01491-8

Internet

https://doi.org/10.1186/s12874-021-01491-8

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