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This is the development version of qsvaR; for the stable release version, see qsvaR.

Generate Quality Surrogate Variable Analysis for Degradation Correction

Bioconductor version: Development (3.20)

The qsvaR package contains functions for removing the effect of degration in rna-seq data from postmortem brain tissue. The package is equipped to help users generate principal components associated with degradation. The components can be used in differential expression analysis to remove the effects of degradation.

Author: Joshua Stolz [aut] , Hedia Tnani [ctb, cre] , Leonardo Collado-Torres [ctb]

Maintainer: Hedia Tnani <hediatnani0 at>

Citation (from within R, enter citation("qsvaR")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))

# The following initializes usage of Bioc devel


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

Introduction to qsvaR HTML R Script
Reference Manual PDF


biocViews BiologicalQuestion, Coverage, DifferentialExpression, Normalization, Sequencing, Software, WorkflowStep
Version 1.9.0
In Bioconductor since BioC 3.15 (R-4.2) (2 years)
License Artistic-2.0
Depends R (>= 4.2), SummarizedExperiment
Imports sva, stats, ggplot2, methods
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Suggests BiocFileCache, BiocStyle, covr, knitr, limma, RefManageR, rmarkdown, sessioninfo, testthat (>= 3.0.0)
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Follow Installation instructions to use this package in your R session.

Source Package qsvaR_1.9.0.tar.gz
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macOS Binary (x86_64) qsvaR_1.9.0.tgz
macOS Binary (arm64) qsvaR_1.9.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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