Bug#955739: marked as done (ITP: r-bioc-sva -- GNU R Surrogate Variable Analysis)
Your message dated Mon, 06 Apr 2020 11:00:13 +0000
with message-id <E1jLPUD-000ArF-9l@fasolo.debian.org>
and subject line Bug#955739: fixed in r-bioc-sva 3.34.0-1
has caused the Debian Bug report #955739,
regarding ITP: r-bioc-sva -- GNU R Surrogate Variable Analysis
to be marked as done.
This means that you claim that the problem has been dealt with.
If this is not the case it is now your responsibility to reopen the
Bug report if necessary, and/or fix the problem forthwith.
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955739: https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=955739
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--- Begin Message ---
Package: wnpp
Severity: wishlist
Subject: ITP: r-bioc-sva -- GNU R Surrogate Variable Analysis
Package: wnpp
Owner: Andreas Tille <tille@debian.org>
Severity: wishlist
* Package name : r-bioc-sva
Version : 3.34.0
Upstream Author : Jeffrey T. Leek <jtleek@gmail.com>, W. Evan Johnson <wej@bu.edu>,
* URL : https://bioconductor.org/packages/sva/
* License : Artistic-2.0
Programming Lang: GNU R
Description : GNU R Surrogate Variable Analysis
The sva package contains functions for removing batch
effects and other unwanted variation in high-throughput
experiment. Specifically, the sva package contains functions
for the identifying and building surrogate variables for
high-dimensional data sets. Surrogate variables are covariates
constructed directly from high-dimensional data (like gene
expression/RNA sequencing/methylation/brain imaging data) that
can be used in subsequent analyses to adjust for unknown,
unmodeled, or latent sources of noise. The sva package can be
used to remove artifacts in three ways: (1) identifying and
estimating surrogate variables for unknown sources of variation
in high-throughput experiments (Leek and Storey 2007 PLoS
Genetics,2008 PNAS), (2) directly removing known batch
effects using ComBat (Johnson et al. 2007 Biostatistics) and (3) removing
batch effects with known control probes (Leek 2014 biorXiv).
Removing batch effects and using surrogate variables in
differential expression analysis have been shown to reduce
dependence, stabilize error rate estimates, and improve
reproducibility, see (Leek and Storey 2007 PLoS Genetics, 2008
PNAS or Leek et al. 2011 Nat. Reviews Genetics).
Remark: This package is maintained by Debian R Packages Maintainers at
https://salsa.debian.org/r-pkg-team/r-bioc-sva
--- End Message ---
--- Begin Message ---
Source: r-bioc-sva
Source-Version: 3.34.0-1
Done: Andreas Tille <tille@debian.org>
We believe that the bug you reported is fixed in the latest version of
r-bioc-sva, which is due to be installed in the Debian FTP archive.
A summary of the changes between this version and the previous one is
attached.
Thank you for reporting the bug, which will now be closed. If you
have further comments please address them to 955739@bugs.debian.org,
and the maintainer will reopen the bug report if appropriate.
Debian distribution maintenance software
pp.
Andreas Tille <tille@debian.org> (supplier of updated r-bioc-sva package)
(This message was generated automatically at their request; if you
believe that there is a problem with it please contact the archive
administrators by mailing ftpmaster@ftp-master.debian.org)
-----BEGIN PGP SIGNED MESSAGE-----
Hash: SHA256
Format: 1.8
Date: Sat, 04 Apr 2020 14:32:57 +0200
Source: r-bioc-sva
Binary: r-bioc-sva r-bioc-sva-dbgsym
Architecture: source amd64
Version: 3.34.0-1
Distribution: unstable
Urgency: medium
Maintainer: Debian R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
Changed-By: Andreas Tille <tille@debian.org>
Description:
r-bioc-sva - GNU R Surrogate Variable Analysis
Closes: 955739
Changes:
r-bioc-sva (3.34.0-1) unstable; urgency=medium
.
* Initial release (closes: #955739)
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