seqgendiff: RNA-Seq Generation/Modification for Simulation

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) <doi:10.1186/s12859-020-3450-9> for details on the implemented methods.

Version: 1.2.2
Imports: assertthat, irlba, sva, pdist, matchingR, clue, cate
Suggests: covr, testthat (≥ 2.1.0), SummarizedExperiment, DESeq2, knitr, rmarkdown, airway, limma, qvalue, edgeR, optmatch
Published: 2020-05-24
Author: David Gerard ORCID iD [aut, cre]
Maintainer: David Gerard <gerard.1787 at>
License: GPL-3
NeedsCompilation: no
Citation: seqgendiff citation info
Materials: README NEWS
CRAN checks: seqgendiff results


Reference manual: seqgendiff.pdf
Vignettes: Applying Different Thinning Functions
Simulate RNA-seq Data from Real Data
Package source: seqgendiff_1.2.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): not available, r-release (x86_64): seqgendiff_1.2.2.tgz, r-oldrel: seqgendiff_1.2.2.tgz
Old sources: seqgendiff archive


Please use the canonical form to link to this page.