RUVnormalize specifications

Information


Unique identifier OMICS_12933
Name RUVnormalize
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License GNU General Public License version 3.0
Computer skills Advanced
Version 1.14.0
Stability Stable
Requirements
R(>=2.10.0), Biobase, RUVnormalizeData
Maintained Yes

Versioning


No version available

Documentation


Maintainer


  • person_outline Laurent Jacob

Publication for RUVnormalize

RUVnormalize citations

 (2)
library_books

Assessment of Single Cell RNA Seq Normalization Methods

2017
PMCID: 5499114
PMID: 28468817
DOI: 10.1534/g3.117.040683

[…] onductor package. The DESeq () method is implemented in the Bioconductor package. For all methods, we ran the R function using default parameters. Remove unwanted variants (RUV) () is included in the RUVnormalize Bioconductor packages. The model sets up a generalized linear regression model between observed RNA-seq read counts and known covariates of interest, along with unknown unwanted variation […]

library_books

Removing Batch Effects from Longitudinal Gene Expression Quantile Normalization Plus ComBat as Best Approach for Microarray Transcriptome Data

2016
PLoS One
PMCID: 4896498
PMID: 27272489
DOI: 10.1371/journal.pone.0156594

[…] odel. Effect estimates were then used to correct batch effects in BLrep samples by rescaling gene expression levels of all probes. For methods v),vi) and vii) R/Bioconductor packages affy, sva [] and RUVnormalize [] were applied to all BLrep and BLFUrep samples. Variation attributable to batch effects before and after batch adjustment were identified using plots of principal component analysis (PC […]

RUVnormalize institution(s)
Laboratoire de Biométrie et Biologie Évolutive, Université de Lyon, Université Lyon 1, CNRS, UMR, Lyon, France; Department of Statistics, University of California, Berkeley, CA, USA; Department of Statistics, University of California, Berkeley, CA, USA; Division of Bioinformatics, Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
RUVnormalize funding source(s)
Supported by the SU2C-AACR-DT0409 grant.

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