Package: SPsimSeq 1.17.0

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_1.17.0.tar.gz
SPsimSeq_1.17.0.zip(r-4.5)SPsimSeq_1.17.0.zip(r-4.4)SPsimSeq_1.17.0.zip(r-4.3)
SPsimSeq_1.17.0.tgz(r-4.4-any)SPsimSeq_1.17.0.tgz(r-4.3-any)
SPsimSeq_1.17.0.tar.gz(r-4.5-noble)SPsimSeq_1.17.0.tar.gz(r-4.4-noble)
SPsimSeq_1.17.0.tgz(r-4.4-emscripten)SPsimSeq_1.17.0.tgz(r-4.3-emscripten)
SPsimSeq.pdf |SPsimSeq.html✨
SPsimSeq/json (API)
NEWS

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

Peer review:

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-1.17.0(bioc 3.21)SPsimSeq-1.16.0(bioc 3.20)

geneexpressionrnaseqsinglecellsequencingdnaseq

7.13 score 10 stars 1 packages 28 scripts 403 downloads 4 mentions 3 exports 135 dependencies

Last updated 2 months agofrom:36e940974b. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 30 2024
R-4.5-winOKNov 30 2024
R-4.5-linuxOKNov 30 2024
R-4.4-winOKNov 30 2024
R-4.4-macOKNov 30 2024
R-4.3-winOKNov 30 2024
R-4.3-macOKNov 30 2024

Exports:configExperimentevaluateDensitiesSPsimSeq

Dependencies:abindade4AnnotationDbiapeaskpassbackportsbase64encBiobaseBiocGenericsbiomformatBiostringsbitbit64blobbslibcachemcheckmatecliclustercodetoolscolorspacecpp11crayoncurldata.tableDBIDelayedArraydigestdoParalleldynamicTreeCutedgeRevaluatefansifarverfastclusterfastmapfitdistrplusfontawesomeforeachforeignFormulafsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2glueGO.dbgridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetshttrigraphimputeIRangesisobanditeratorsjquerylibjsonliteKEGGRESTknitrlabelinglatticelifecyclelimmalocfitmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimemulttestmunsellmvtnormnlmennetopensslpermutephyloseqpillarpixmappkgconfigplogrplyrpngpreprocessCoreR6rappdirsRColorBrewerRcppRcppArmadilloreshape2rhdf5rhdf5filtersRhdf5librlangrmarkdownrpartRSQLiterstudioapiS4ArraysS4VectorssassscalesSingleCellExperimentspSparseArraystatmodstringistringrSummarizedExperimentsurvivalsystibbletinytexUCSC.utilsutf8vctrsveganviridisviridisLiteWGCNAwithrxfunXVectoryamlzlibbioc

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

Rendered fromSPsimSeq.Rmdusingknitr::rmarkdownon Nov 30 2024.

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