Package: SPsimSeq 1.22.0

Joris Meys

SPsimSeq: Semi-parametric simulation tool for bulk and single-cell RNA sequencing data

SPsimSeq uses a specially designed exponential family for density estimation to constructs the distribution of gene expression levels from a given real RNA sequencing data (single-cell or bulk), and subsequently simulates a new dataset from the estimated marginal distributions using Gaussian-copulas to retain the dependence between genes. It allows simulation of multiple groups and batches with any required sample size and library size.

Authors:Alemu Takele Assefa [aut], Olivier Thas [ths], Joris Meys [cre], Stijn Hawinkel [aut]

SPsimSeq_1.22.0.tar.gz
SPsimSeq_1.22.0.zip(r-4.7)SPsimSeq_1.22.0.zip(r-4.6)SPsimSeq_1.22.0.zip(r-4.5)
SPsimSeq_1.22.0.tgz(r-4.6-any)SPsimSeq_1.22.0.tgz(r-4.5-any)
SPsimSeq_1.22.0.tar.gz(r-4.7-any)SPsimSeq_1.22.0.tar.gz(r-4.6-any)
SPsimSeq_1.22.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
SPsimSeq/json (API)
NEWS

# Install 'SPsimSeq' in R:
install.packages('SPsimSeq', repos = c('https://bioc-release.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/centerforstatistics-ugent/spsimseq/issues

Datasets:
  • scNGP.data - Neuroblastoma NGP cells single-cell RNA-seq.
  • zhang.data.sub - Neuroblastoma bulk RNA-seq data retrieved from Zhang et (2015).

On BioConductor:SPsimSeq-1.23.0(bioc 3.24)SPsimSeq-1.22.0(bioc 3.23)

geneexpressionrnaseqsinglecellsequencingdnaseq

7.19 score 10 stars 1 packages 32 scripts 293 downloads 4 mentions 3 exports 109 dependencies

Last updated from:f8eff70dce (on RELEASE_3_23). Checks:1 NOTE, 9 OK. Indexed: no.

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source / vignettesOK413
linux-release-x86_64OK478
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macos-oldrel-arm64OK258
windows-develOK356
windows-releaseOK353
windows-oldrelOK364
wasm-releaseOK165

Exports:configExperimentevaluateDensitiesSPsimSeq

Dependencies:abindade4apebackportsbase64encBiobaseBiocGenericsbiomformatBiostringsbslibcachemcheckmatecliclustercodetoolscolorspacecpp11crayondata.tableDelayedArraydigestdoParalleldynamicTreeCutedgeRevaluatefarverfastclusterfastmapfitdistrplusfontawesomeforeachforeignFormulafsgenericsGenomicRangesggplot2gluegridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetsigraphimputeIRangesisobanditeratorsjquerylibjsonliteknitrlabelinglatticelifecyclelimmalocfitmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimemulttestmvtnormnlmennetpermutephyloseqpixmappkgconfigplyrpreprocessCoreR6rappdirsRColorBrewerRcppRcppArmadilloreshape2rlangrmarkdownrpartrstudioapiS4ArraysS4VectorsS7sassscalesSeqinfoSingleCellExperimentspSparseArraystatmodstringistringrSummarizedExperimentsurvivaltinytexvctrsveganviridisLiteWGCNAwithrxfunXVectoryaml

Manual for the SPsimSeq package: semi-parametric simulation for bulk and single cell RNA-seq data

Rendered fromSPsimSeq.Rmdusingknitr::rmarkdownon Jun 02 2026.

Last update: 2020-05-15
Started: 2020-04-01

Readme and manuals

Help Manual

Help pageTopics
SPsimSeq packageSPsimSeq-package
An auxialiary function to quickly construct the polyomial matrix, using Horner's rulebuildXmat
Calculates counts per millions of reads, possibly with log-transformcalculateCPM
Check for data validitycheckInputValidity
Select candidate geneschooseCandGenes
Configure experimentconfigExperiment
Construct the cumulative densityconstructDens
Estimate log-normal distribution for the library sizesestLibSizeDistr
Evaluate the densities in the estimated SPsimSeq objectevaluateDensities
Evaluate the expit functionexpit
A function with S4 dispatching to extract the count matrixextractMat extractMat,data.frame-method extractMat,matrix-method extractMat,phyloseq-method extractMat,SingleCellExperiment-method
Fit log linear model for each genefitLLmodel
Fast fit Poisson regressionfitPoisGlm
Extract data and iterate over batches to estimate zero probability modelsfracZeroLogitModel
Generate a copula instancegenCopula
Gene level param estimates for density estimationgeneParmEst
Generate library sizes from log-normalgenLibSizes
Match copulas to estimated SP distributionmatchCopula
A function to obtain copulas or uniform random variablesobtCorMatsBatch
Calculates height and mid points of a distributionobtCount
Density estimation on a single vectorparmEstDensVec
A function to prepare outputsprepareSPsimOutputs
Return ID for observations to be set to zerosamZeroID
Neuroblastoma NGP cells single-cell RNA-seq.scNGP.data
Sample genes from candidate genesselectGenes
A function that generates the simulated data for a single geneSPsimPerGene
A function to simulate bulk or single cell RNA sequencing dataSPsimSeq
Predict zero probability using logistic rgressionzeroProbModel
Neuroblastoma bulk RNA-seq data retrieved from Zhang et (2015).zhang.data.sub