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Provides a background correction method which uses a mixture of exponential and truncated normal distributions to flexibly model signal intensity and uses a truncated normal distribution to model background noise. Depending on data availability, three approaches are employed to estimate background normal distribution parameters using (i) internal chip negative controls, (ii) out-of-band Infinium I probe intensities or (iii) combined methylated and unmethylated intensities. Evaluation results in both duplicates and experimental standard samples showed that ENmix outperformed commonly used background subtraction methods in terms of improvement in replicability and accuracy as well as reducing probe design bias. After ENmix background correction the resulting data can be used with other commonly-used preprocessing methods including quantile normalization for between-sample normalization and BMIQ for further correction of probe-design bias.

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ENmix classification

ENmix specifications

Software type:
Restrictions to use:
Operating system:
Unix/Linux, Mac OS, Windows
Artistic License version 2.0
minfi, parallel, doParallel, Biobase, foreach
Command line interface
Biological technology:
Programming languages:
Computer skills:

ENmix distribution


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ENmix support



  • Zongli Xu <>


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Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA; Biostatistics & Computational Biology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA; Department of Environmental Health, College of Medicine, University of Cincinnati, Cincinnati, OH, USA; Laboratory of Molecular Carcinogenesis, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA

Funding source(s)

Intramural Research Program of the NIH, National Institute of Environmental Health Sciences [Z01 ES044005, Z01 ES101765, Z01 ES049033, Z01 ES049032]

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