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NanoStringDiff

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Offers a comprehensive and general framework to characterize NanoString nCounter data and to detect differential expression (DE) genes for both simple and complex experimental designs. As a method specifically designed for nCounter data, NanoStringDiff utilizes a negative binomial-based model to fit the discrete nature of the data and incorporates several normalization parameters in the model to fully adjust for platform source of variation, sample content variation and background noise. Simulation and real data analyses results show that NanoStringDiff outperforms the existing methods in DE detection.

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NanoStringDiff versioning

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NanoStringDiff classification

NanoStringDiff specifications

Software type:
Package/Module
Restrictions to use:
None
Programming languages:
R
Computer skills:
Advanced
Stability:
Stable
Source code URL:
https://github.com/Bioconductor-mirror/NanoStringDiff/tree/release-3.3
Interface:
Command line interface
Operating system:
Unix/Linux, Mac OS, Windows
License:
GNU General Public License version 3.0
Version:
1.2.0
Requirements:
Biobase
Maintained:
Yes

NanoStringDiff support

Documentation

Maintainer

  • Hong Wang <>

Credits

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Publications

Institution(s)

Department of Statistics, University of Kentucky, Lexington, KY, USA; Departments of Pathology and Neurosurgery, Northwestern University, Chicago, IL, USA; Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, USA; Department of Pathology and Laboratory Medicine, University of Kentucky, Lexington, KY, USA; Paul Laurence Dunbar High School, Lexington, KY, USA; Biostatistics and Bioinformatics Shared Resource Facility, Markey Cancer Center, University of Kentucky, Lexington, KY, USA; Department of Biostatistics, University of Kentucky, Lexington, KY, USA

Funding source(s)

National Cancer Institute Cancer Center Support Grant [P30CA177558]; Institutional Development Award (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health [5P20GM103436-15]

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