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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/AllClasses.R
\docType{class}
\name{SplatParams}
\alias{SplatParams}
\alias{SplatParams-class}
\title{The SplatParams class}
\description{
S4 class that holds parameters for the Splatter simulation.
}
\section{Parameters}{
The Splatter simulation requires the following parameters:
\describe{
\item{\code{nGenes}}{The number of genes to simulate.}
\item{\code{nCells}}{The number of cells to simulate.}
\item{\code{[nGroups]}}{The number of groups or paths to simulate.}
\item{\code{[groupCells]}}{Vector giving the number of cells in each
simulation group/path.}
\item{\code{[seed]}}{Seed to use for generating random numbers.}
\item{\emph{Mean parameters}}{
\describe{
\item{\code{mean.shape}}{Shape parameter for the mean gamma
distribution.}
\item{\code{mean.rate}}{Rate parameter for the mean gamma
distribution.}
}
}
\item{\emph{Library size parameters}}{
\describe{
\item{\code{lib.loc}}{Location (meanlog) parameter for the
library size log-normal distribution.}
\item{\code{lib.scale}}{Scale (sdlog) parameter for the library
size log-normal distribution.}
}
}
\item{\emph{Expression outlier parameters}}{
\describe{
\item{\code{out.prob}}{Probability that a gene is an expression
outlier.}
\item{\code{out.facLoc}}{Location (meanlog) parameter for the
expression outlier factor log-normal distribution.}
\item{\code{out.facScale}}{Scale (sdlog) parameter for the
expression outlier factor log-normal distribution.}
}
}
\item{\emph{Differential expression parameters}}{
\describe{
\item{\code{[de.prob]}}{Probability that a gene is differentially
expressed in a group. Can be a vector.}
\item{\code{[de.loProb]}}{Probability that a differentially
expressed gene is down-regulated. Can be a vector.}
\item{\code{[de.facLoc]}}{Location (meanlog) parameter for the
differential expression factor log-normal distribution. Can be a
vector.}
\item{\code{[de.facScale]}}{Scale (sdlog) parameter for the
differential expression factor log-normal distribution. Can be a
vector.}
}
}
\item{\emph{Biological Coefficient of Variation parameters}}{
\describe{
\item{\code{bcv.common}}{Underlying common dispersion across all
genes.}
\item{\code{bcv.df}}{Degrees of Freedom for the BCV inverse
chi-squared distribution.}
}
}
\item{\emph{Dropout parameters}}{
\describe{
\item{\code{dropout.present}}{Logical. Whether to simulate
dropout.}
\item{\code{dropout.mid}}{Midpoint parameter for the dropout
logistic function.}
\item{\code{dropout.shape}}{Shape parameter for the dropout
logistic function.}
}
}
\item{\emph{Differentiation path parameters}}{
\describe{
\item{\code{[path.from]}}{Vector giving the originating point of
each path. This allows path structure such as a cell type which
differentiates into an intermediate cell type that then
differentiates into two mature cell types. A path structure of
this form would have a "from" parameter of c(0, 1, 1) (where 0 is
the origin). If no vector is given all paths will start at the
origin.}
\item{\code{[path.length]}}{Vector giving the number of steps to
simulate along each path. If a single value is given it will be
applied to all paths.}
\item{\code{[path.skew]}}{Vector giving the skew of each path.
Values closer to 1 will give more cells towards the starting
population, values closer to 0 will give more cells towards the
final population. If a single value is given it will be applied
to all paths.}
\item{\code{[path.nonlinearProb]}}{Probability that a gene
follows a non-linear path along the differentiation path. This
allows more complex gene patterns such as a gene being equally
expressed at the beginning an end of a path but lowly expressed
in the middle.}
\item{\code{[path.sigmaFac]}}{Sigma factor for non-linear gene
paths. A higher value will result in more extreme non-linear
variations along a path.}
}
}
}
The parameters not shown in brackets can be estimated from real data using
\code{\link{splatEstimate}}. For details of the Splatter simulation
see \code{\link{splatSimulate}}.
}