% 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}}.
}