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RUVnormalize specifications


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
R(>=2.10.0), Biobase, RUVnormalizeData
Maintained Yes


No version available



  • person_outline Laurent Jacob <>

Publication for RUVnormalize

RUVnormalize citations


Assessment of Single Cell RNA Seq Normalization Methods

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

[…] 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 […]


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

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

[…] estimates were then used to correct batch effects in blrep measurements 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 measurements. different linear regression models were applied to estimate a linear equation, which was subsequently used to rescale gene […]

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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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