Alternative empirical Bayes models for adjusting for batch effects in genomic studies

Abstract Background Combining genomic data sets from multiple studies is advantageous to increase statistical power in studies where logistical considerations restrict sample size or require the sequential generation of data. However, significant technical heterogeneity is commonly observed across m...

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Hauptverfasser: Yuqing Zhang, David F. Jenkins, Solaiappan Manimaran, W. Evan Johnson
Format: Artigo
Sprache:Inglês
Veröffentlicht: BMC 2018-07-01
Schriftenreihe:BMC Bioinformatics
Schlagworte:
Batch effects
Empirical Bayes models
Data integration
Biomarker development
Online Zugang:http://link.springer.com/article/10.1186/s12859-018-2263-6
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