LCox: a tool for selecting genes related to survival outcomes using longitudinal gene expression data

DOI10.1515/sagmb-2017-0060zbMath1420.92034OpenAlexW2912224309WikidataQ91545666 ScholiaQ91545666MaRDI QIDQ2324979

Naftali Kaminski, Jose D. Herazo-Maya, Hongyu Zhao, Jiehuan Sun, Jane-Ling Wang

Publication date: 12 September 2019

Published in: Statistical Applications in Genetics and Molecular Biology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/sagmb-2017-0060

zbMATH Keywords

biomarker identificationlongitudinal gene expression datasurvival outcomes

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Biochemistry, molecular biology (92C40)

Related Items (1)

LCox

Uses Software

• R
• MSigDB

Cites Work

• Unnamed Item
• Random survival forests
• Optimal estimation for the functional Cox model
• Variable selection for Cox's proportional hazards model and frailty model
• L₁Penalized Estimation in the Cox Proportional Hazards Model
• Kernel Machine Approach to Testing the Significance of Multiple Genetic Markers for Risk Prediction
• A Direct Approach to False Discovery Rates
• Joint Modeling of Survival and Longitudinal Data: Likelihood Approach Revisited
• Functional Data Analysis for Sparse Longitudinal Data

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