<?xml version="1.0" encoding="UTF-8"?>
<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>RNA-Seq Generation/Modification for Simulation</dc:title>
  <dc:title>R package seqgendiff version 1.2.4</dc:title>
  <dc:subject>CRAN Task View: Omics (https://CRAN.R-project.org/view=Omics)</dc:subject>
  <dc:description>Generates/modifies RNA-seq data for use in simulations. We provide
    a suite of functions that will add a known amount of signal to a real 
    RNA-seq dataset. The advantage of using this approach over simulating under
    a theoretical distribution is that common/annoying aspects of the data
    are more preserved, giving a more realistic evaluation of your method. 
    The main functions are select_counts(), thin_diff(), thin_lib(), 
    thin_gene(), thin_2group(), thin_all(), and effective_cor(). See
    Gerard (2020) &lt;doi:10.1186/s12859-020-3450-9&gt; for details on the
    implemented methods.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Imports: assertthat, irlba, sva, pdist, matchingR, clue</dc:relation>
  <dc:relation>Suggests: covr, testthat (&gt;= 2.1.0), SummarizedExperiment, DESeq2,
knitr, rmarkdown, airway, limma, qvalue, edgeR</dc:relation>
  <dc:creator>David Gerard &lt;gerard.1787@gmail.com&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>David Gerard [aut, cre] (ORCID:
    &lt;https://orcid.org/0000-0001-9450-5023&gt;)</dc:contributor>
  <dc:rights>GPL-3</dc:rights>
  <dc:date>2024-05-15</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=seqgendiff</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.seqgendiff</dc:identifier>
</oai_dc:dc>
