% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/allgenerics.R, R/processing.R
\name{normalizeData}
\alias{normalizeData}
\alias{normalizeData,VoltRon-method}
\alias{normalizeData,vrAssay-method}
\alias{normalizeData,vrAssayV2-method}
\title{Normalize Data}
\usage{
normalizeData(object, ...)

\S4method{normalizeData}{VoltRon}(
  object,
  assay = NULL,
  method = "LogNorm",
  desiredQuantile = 0.9,
  scale = 0.2,
  sizefactor = 10000,
  feat_type = NULL
)

\S4method{normalizeData}{vrAssay}(
  object,
  method = "LogNorm",
  desiredQuantile = 0.9,
  scale = 0.2,
  sizefactor = 10000,
  feat_type = NULL
)

\S4method{normalizeData}{vrAssayV2}(
  object,
  method = "LogNorm",
  desiredQuantile = 0.9,
  scale = 0.2,
  sizefactor = 10000,
  feat_type = NULL
)
}
\arguments{
\item{object}{a VoltRon or vrAssay object.}

\item{...}{arguments passed to other methods.}

\item{assay}{assay name (exp: Assay1) or assay class (exp: Visium, Xenium), see \link{SampleMetadata}. 
if NULL, the default assay will be used, see \link{vrMainAssay}.}

\item{method}{the normalization method: "LogNorm", "Q3Norm", "LogQ3Norm" or "CLR"}

\item{desiredQuantile}{the quantile of the data if "QuanNorm" or "LogQuanNorm" is selected as \code{method}.}

\item{scale}{the scale parameter for the hyperbolic arcsine transformation}

\item{sizefactor}{size factor if \code{method} is selected as \code{LogNorm}}

\item{feat_type}{the feature set type}
}
\description{
Given a VoltRon or vrAssay object, normalize the raw count data.
}