Improving predictive models for Alzheimer's disease using GWAS data by incorporating misclassified samples modeling.
Late-onset Alzheimer's Disease (LOAD) is the most common form of dementia in the elderly. Genome-wide association studies (GWAS) for LOAD have open new avenues to identify genetic causes and to provide diagnostic tools for early detection. Although several predictive models have been proposed u...
Main Authors: | Brissa-Lizbeth Romero-Rosales, Jose-Gerardo Tamez-Pena, Humberto Nicolini, Maria-Guadalupe Moreno-Treviño, Victor Trevino |
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Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2020-01-01
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Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0232103 |
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