r-bioc-qusage 2.30.0-1 source package in Ubuntu


r-bioc-qusage (2.30.0-1) unstable; urgency=medium

  * Team upload.
  * New upstream version
  * Standards-Version: 4.6.1 (routine-update)

 -- Andreas Tille <email address hidden>  Fri, 13 May 2022 15:04:19 +0200

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Debian R Packages Maintainers
Medium Urgency

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Series Pocket Published Component Section
Kinetic release universe misc


Kinetic: [FULLYBUILT] amd64


File Size SHA-256 Checksum
r-bioc-qusage_2.30.0-1.dsc 2.1 KiB 1851f9247d4e4e8450a0afa347eed3ce8d73a90977e691fe803ce018d0b7c54c
r-bioc-qusage_2.30.0.orig.tar.gz 9.5 MiB 4160708f7132d3c41eaa988cf83575d873a65ad7804e571306aca0743c824c52
r-bioc-qusage_2.30.0-1.debian.tar.xz 3.1 KiB a0e17e2128b2b58c385043e5fa8082ff1905a58a3804759cb45488db97ccaf53

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Binary packages built by this source

r-bioc-qusage: qusage: Quantitative Set Analysis for Gene Expression

 This package is an implementation the Quantitative Set
 Analysis for Gene Expression (QuSAGE) method described in
 (Yaari G. et al, Nucl Acids Res, 2013). This is a novel Gene
 Set Enrichment-type test, which is designed to provide a
 faster, more accurate, and easier to understand test for gene
 expression studies. qusage accounts for inter-gene correlations
 using the Variance Inflation Factor technique proposed by Wu et
 al. (Nucleic Acids Res, 2012). In addition, rather than simply
 evaluating the deviation from a null hypothesis with a single
 number (a P value), qusage quantifies gene set activity with a
 complete probability density function (PDF). From this PDF, P
 values and confidence intervals can be easily extracted.
 Preserving the PDF also allows for post-hoc analysis (e.g.,
 pair-wise comparisons of gene set activity) while maintaining
 statistical traceability. Finally, while qusage is compatible
 with individual gene statistics from existing methods (e.g.,
 LIMMA), a Welch-based method is implemented that is shown to
 improve specificity. For questions, contact Chris Bolen
 (cbolen1@gmail.com) or Steven Kleinstein