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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Hlavní autoři: Yuqing Zhang, David F. Jenkins, Solaiappan Manimaran, W. Evan Johnson
Médium: Artigo
Jazyk:Inglês
Vydáno: BMC 2018-07-01
Edice:BMC Bioinformatics
Témata:
Batch effects
Empirical Bayes models
Data integration
Biomarker development
On-line přístup:http://link.springer.com/article/10.1186/s12859-018-2263-6
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