Testing the significance of cell-cycle patterns in time-course microarray data using nonparametric quadratic inference functions

DOI10.1016/J.CSDA.2007.03.018zbMath1452.62854OpenAlexW2083519741MaRDI QIDQ1023465

Guei-Feng Tsai, Annie Qu

Publication date: 12 June 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2007.03.018

zbMATH Keywords

chi-squared testquadratic inference functionvarying coefficient modelcell-cycle microarray datagene grouping

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Biochemistry, molecular biology (92C40)

Related Items (2)

Distance-correlation based gene set analysis in longitudinal studies ⋮ Editorial: Statistical genetics \& statistical genomics: where biology, epistemology, statistics, and computation collide

Cites Work

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• Large Sample Properties of Generalized Method of Moments Estimators
• Longitudinal data analysis using generalized linear models
• Improving generalised estimating equations using quadratic inference functions
• Clustering of unevenly sampled gene expression time-series data
• Statistical modeling of large microarray data sets to identify stimulus-response profiles
• Varying-coefficient models and basis function approximations for the analysis of repeated measurements
• Quadratic Inference Functions for Varying‐Coefficient Models with Longitudinal Data
• The Clustering of Regression Models Method with Applications in Gene Expression Data

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