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<h1>List simulations</h1>
<small class="dont-index">Source: <a href='https://github.com/Oshlack/splatter/blob/master/R/listSims.R'><code>R/listSims.R</code></a></small>
<div class="hidden name"><code>listSims.Rd</code></div>
</div>
<div class="ref-description">
<p>List all the simulations that are currently available in Splatter with a
brief description.</p>
</div>
<pre class="usage"><span class='fu'>listSims</span>(<span class='kw'>print</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>print</th>
<td><p>logical. Whether to print to the console.</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>Invisibly returns a data.frame containing the information that is
displayed.</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='fu'>listSims</span>()</div><div class='output co'>#> Splatter currently contains 13 simulations
#>
#> Splat (splat)
#> DOI: 10.1186/s13059-017-1305-0 GitHub: Oshlack/splatter
#> 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.
#>
#> Splat Single (splatSingle)
#> DOI: 10.1186/s13059-017-1305-0 GitHub: Oshlack/splatter
#> The Splat simulation with a single population.
#>
#> Splat Groups (splatGroups)
#> DOI: 10.1186/s13059-017-1305-0 GitHub: Oshlack/splatter
#> The Splat simulation with multiple groups. Each group can have it's own differential expression probability and fold change distribution.
#>
#> Splat Paths (splatPaths)
#> DOI: 10.1186/s13059-017-1305-0 GitHub: Oshlack/splatter
#> The Splat simulation with differentiation paths. Each path can have it's own length, skew and probability. Genes can change in non-linear ways.
#>
#> Simple (simple)
#> DOI: 10.1186/s13059-017-1305-0 GitHub: Oshlack/splatter
#> A simple simulation with gamma means and negative binomial counts.
#>
#> Lun (lun)
#> DOI: 10.1186/s13059-016-0947-7 GitHub: MarioniLab/Deconvolution2016
#> Gamma distributed means and negative binomial counts. Cells are given a size factor and differential expression can be simulated with fixed fold changes.
#>
#> Lun 2 (lun2)
#> DOI: 10.1093/biostatistics/kxw055 GitHub: MarioniLab/PlateEffects2016
#> 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.
#>
#> scDD (scDD)
#> DOI: 10.1186/s13059-016-1077-y GitHub: kdkorthauer/scDD
#> The scDD simulation samples a given dataset and can simulate differentially expressed and differentially distributed genes between two conditions.
#>
#> BASiCS (BASiCS)
#> DOI: 10.1371/journal.pcbi.1004333 GitHub: catavallejos/BASiCS
#> The BASiCS simulation is based on a bayesian model used to deconvolve biological and technical variation and includes spike-ins and batch effects.
#>
#> mfa (mfa)
#> DOI: 10.12688/wellcomeopenres.11087.1 GitHub: kieranrcampbell/mfa
#> The mfa simulation produces a bifurcating pseudotime trajectory. This can optionally include genes with transient changes in expression and added dropout.
#>
#> PhenoPath (pheno)
#> DOI: 10.1101/159913 GitHub: kieranrcampbell/phenopath
#> The PhenoPath simulation produces a pseudotime trajectory with different types of genes.
#>
#> ZINB-WaVE (zinb)
#> DOI: 10.1101/125112 GitHub: drisso/zinbwave
#> The ZINB-WaVE simulation simulates counts from a sophisticated zero-inflated negative-binomial distribution including cell and gene-level covariates.
#>
#> SparseDC (sparseDC)
#> DOI: 10.1093/nar/gkx1113 GitHub: cran/SparseDC
#> The SparseDC simulation simulates a set of clusters across two conditions, where some clusters may be present in only one condition.
#> </div></pre>
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<h2>Contents</h2>
<ul class="nav nav-pills nav-stacked">
<li><a href="#arguments">Arguments</a></li>
<li><a href="#value">Value</a></li>
<li><a href="#examples">Examples</a></li>
</ul>
</div>
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