Unfolding of hidden white blood cell count phenotypes for gene discovery using latent class mixed modeling.
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ABSTRACT:
SUBMITTER: Hall TO
PROVIDER: S-EPMC6541537 | biostudies-literature | 2019 Sep
REPOSITORIES: biostudies-literature
Publications
Unfolding of hidden white blood cell count phenotypes for gene discovery using latent class mixed modeling.
Hall Taryn O TO Stanaway Ian B IB Carrell David S DS Carroll Robert J RJ Denny Joshua C JC Hakonarson Hakon H Larson Eric B EB Mentch Frank D FD Peissig Peggy L PL Pendergrass Sarah A SA Rosenthal Elisabeth A EA Jarvik Gail P GP Crosslin David R DR
Genes and immunity 20181121 7
Resting-state white blood cell (WBC) count is a marker of inflammation and immune system health. There is evidence that WBC count is not fixed over time and there is heterogeneity in WBC trajectory that is associated with morbidity and mortality. Latent class mixed modeling (LCMM) is a method that can identify unobserved heterogeneity in longitudinal data and attempts to classify individuals into groups based on a linear model of repeated measurements. We applied LCMM to repeated WBC count measu ...[more]
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