r-bioc-qusage 2.28.0-1 source package in Ubuntu


r-bioc-qusage (2.28.0-1) unstable; urgency=medium

  * Team upload.
  * New upstream version 2.28.0

 -- Nilesh Patra <email address hidden>  Wed, 24 Nov 2021 21:14:51 +0530

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Debian R Packages Maintainers
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Debian R Packages Maintainers
Medium Urgency

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Series Pocket Published Component Section
Kinetic release universe misc
Jammy release universe misc


Jammy: [FULLYBUILT] amd64


File Size SHA-256 Checksum
r-bioc-qusage_2.28.0-1.dsc 2.1 KiB e9ed4d755c2fade31997693df99b02952a5430d1725365a6512373be551603e6
r-bioc-qusage_2.28.0.orig.tar.gz 9.5 MiB 05d7d171b24aaf8eb2dd743c03211843cf59bf555c3c633616c282e7f3722bae
r-bioc-qusage_2.28.0-1.debian.tar.xz 3.1 KiB 8dfbfdab7cf88b6c926e82a00c3576e8001c6228b16c274f02eff3a393eae235

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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