List all the simulations that are currently available in Splatter with a brief description.
Examples
listSims()
#> Splatter currently contains 15 simulations
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#> Splat (splat)
#> DOI: 10.1186/s13059-017-1305-0 GitHub: Oshlack/splatter Dependencies:
#> The Splat simulation generates means from a gamma distribution, adjusts them for BCV and generates counts from a gamma-poisson. Dropout and batch effects can be optionally added.
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#> Splat Single (splatSingle)
#> DOI: 10.1186/s13059-017-1305-0 GitHub: Oshlack/splatter Dependencies:
#> The Splat simulation with a single population.
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#> Splat Groups (splatGroups)
#> DOI: 10.1186/s13059-017-1305-0 GitHub: Oshlack/splatter Dependencies:
#> The Splat simulation with multiple groups. Each group can have it's own differential expression probability and fold change distribution.
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#> Splat Paths (splatPaths)
#> DOI: 10.1186/s13059-017-1305-0 GitHub: Oshlack/splatter Dependencies:
#> The Splat simulation with differentiation paths. Each path can have it's own length, skew and probability. Genes can change in non-linear ways.
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#> Kersplat (kersplat)
#> DOI: GitHub: Oshlack/splatter Dependencies: scuttle, igraph
#> The Kersplat simulation extends the Splat model by adding a gene network, more complex cell structure, doublets and empty cells (Experimental).
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#> splatPop (splatPop)
#> DOI: 10.1186/s13059-021-02546-1 GitHub: Oshlack/splatter Dependencies: VariantAnnotation, preprocessCore
#> The splatPop simulation enables splat simulations to be generated for multiple individuals in a population, accounting for correlation structure by simulating expression quantitative trait loci (eQTL).
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#> Simple (simple)
#> DOI: 10.1186/s13059-017-1305-0 GitHub: Oshlack/splatter Dependencies:
#> A simple simulation with gamma means and negative binomial counts.
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#> Lun (lun)
#> DOI: 10.1186/s13059-016-0947-7 GitHub: MarioniLab/Deconvolution2016 Dependencies:
#> Gamma distributed means and negative binomial counts. Cells are given a size factor and differential expression can be simulated with fixed fold changes.
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#> Lun 2 (lun2)
#> DOI: 10.1093/biostatistics/kxw055 GitHub: MarioniLab/PlateEffects2016 Dependencies: scran, scuttle, lme4, pscl, limSolve
#> Negative binomial counts where the means and dispersions have been sampled from a real dataset. The core feature of the Lun 2 simulation is the addition of plate effects. Differential expression can be added between two groups of plates and optionally a zero-inflated negative-binomial can be used.
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#> scDD (scDD)
#> DOI: 10.1186/s13059-016-1077-y GitHub: kdkorthauer/scDD Dependencies: scDD
#> The scDD simulation samples a given dataset and can simulate differentially expressed and differentially distributed genes between two conditions.
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#> BASiCS (BASiCS)
#> DOI: 10.1371/journal.pcbi.1004333 GitHub: catavallejos/BASiCS Dependencies: BASiCS
#> The BASiCS simulation is based on a bayesian model used to deconvolve biological and technical variation and includes spike-ins and batch effects.
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#> mfa (mfa)
#> DOI: 10.12688/wellcomeopenres.11087.1 GitHub: kieranrcampbell/mfa Dependencies: mfa
#> The mfa simulation produces a bifurcating pseudotime trajectory. This can optionally include genes with transient changes in expression and added dropout.
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#> PhenoPath (pheno)
#> DOI: 10.1038/s41467-018-04696-6 GitHub: kieranrcampbell/phenopath Dependencies: phenopath
#> The PhenoPath simulation produces a pseudotime trajectory with different types of genes.
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#> ZINB-WaVE (zinb)
#> DOI: 10.1038/s41467-017-02554-5 GitHub: drisso/zinbwave Dependencies: zinbwave
#> The ZINB-WaVE simulation simulates counts from a sophisticated zero-inflated negative-binomial distribution including cell and gene-level covariates.
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#> SparseDC (sparseDC)
#> DOI: 10.1093/nar/gkx1113 GitHub: cran/SparseDC Dependencies: SparseDC
#> The SparseDC simulation simulates a set of clusters across two conditions, where some clusters may be present in only one condition.
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