% 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.

}