Exploiting blank spots for model-based background correction in discovering genes with DNA array data

DOI10.1177/1471082X1001100201OpenAlexW1969441159MaRDI QIDQ4970597

Serena Arima, Francesca Mariani, Brunero Liseo, Luca Tardella

Publication date: 7 October 2020

Published in: Statistical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1177/1471082x1001100201

zbMATH Keywords

differential expressionBayesian hierarchical modelgene expression databackground correctionblank spotsnormalization issues

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• R
• WinBUGS

Cites Work

• Unnamed Item
• Unnamed Item
• The analysis of gene expression data. Methods and software
• Posterior predictive \(p\)-values
• Significance analysis of microarrays applied to the ionizing radiation response
• When should one subtract background fluorescence in 2-color microarrays?
• DNA Microarray Experiments: Biological and Technological Aspects
• Statistical Applications of the Multivariate Skew Normal Distribution
• P Values for Composite Null Models
• Statistics for Microarrays
• Bayesian Modeling of Differential Gene Expression
• Detecting differential gene expression with a semiparametric hierarchical mixture method
• Quality Control and Robust Estimation for cDNA Microarrays With Replicates
• A Bayesian Mixture Model for Differential Gene Expression
• Bayesian Inference for Gene Expression and Proteomics

This page was built for publication: Exploiting blank spots for model-based background correction in discovering genes with DNA array data