Statistical method for modeling sequencing data from different technologies in longitudinal studies with application to Huntington disease

DOI10.1002/bimj.201900235zbMath1523.62116OpenAlexW3118216728WikidataQ104555942 ScholiaQ104555942MaRDI QIDQ6071002

Unnamed Author, Unnamed Author, Hae-Won Uh, Unnamed Author, Jeanine J. Houwing-Duistermaat

Publication date: 27 November 2023

Published in: Biometrical Journal (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/1887/3184673

zbMATH Keywords

quality controlmeasurement errorRNA-seqlinear mixed modelDeepSAGE

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Mixtures of linear regressions
• Probabilistic partial least squares model: identifiability, estimation and application
• Measurement errors, linear calibration and inferences for means
• Response error in a transformation model with an application to earnings‐equation estimation*
• Measurement Error in the Response in the General Linear Model
• Statistical Analysis of Financial Data in S-Plus
• Measurement Error
• Correcting for nonlinear measurement errors in the dependent variable in the general linear model
• Measurement Error in Nonlinear Models
• Linear mixed models for longitudinal data

This page was built for publication: Statistical method for modeling sequencing data from different technologies in longitudinal studies with application to Huntington disease