Variance function estimation in quantitative mass spectrometry with application to iTRAQ labeling

DOI10.1214/12-AOAS572zbMath1454.62359arXiv1304.4433OpenAlexW3098440178MaRDI QIDQ1951515

Manor Askenazi, Jarrod A. Marto, Yi Zhang, Micha Mandel

Publication date: 6 June 2013

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1304.4433

zbMATH Keywords

heteroscedasticitynuisance parametermixture modelproteomicsiTRAQ

Mathematics Subject Classification ID

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

Related Items (1)

Variance function estimation in quantitative mass spectrometry with application to iTRAQ labeling

Uses Software

• R

Cites Work

• Nonparametric estimation of genewise variance for microarray data
• Identifiability of continuous mixtures of unknown Gaussian distributions
• A reliable method of estimating the variance function in immunoassay
• Variance function estimation in quantitative mass spectrometry with application to iTRAQ labeling
• Variance Estimation in the Analysis of Microarray Data
• Consistency of the Maximum Likelihood Estimator in the Presence of Infinitely Many Incidental Parameters
• A RESTRICTED MAXIMUM LIKELIHOOD PROCEDURE FOR ESTIMATING THE VARIANCE FUNCTION OF AN IMMUNOASSAY
• Nonparametric variance estimation in the analysis of microarray data: a measurement error approach
• Variance Function Estimation
• P Values Maximized Over a Confidence Set for the Nuisance Parameter
• Consistent Estimates Based on Partially Consistent Observations

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