\title{loess_normalization}
\usage{
loess_normalization(expressions, iterations = 2, small.positive = 0.1,
- sample.size = 200, num.cores = max(floor(detectCores()/2), 1),
- normalization.method = "mean")
+ sample.size = 200, num.cores = max(floor(parallel::detectCores()/2), 1),
+ imputation.method = "mean", offset = 0)
}
\arguments{
\item{expressions}{Gene expression values with probes in rows and samples in columns}
\item{num.cores}{Number of cores to use (Default: half of them)}
-\item{noramlization.method}{Normalization method (Default: mean).}
+\item{imputation.method}{Method to impute missing values. String of "mean" (missing values are the mean of the row) or "knn" (use impute.knn to impute missing values) (Default: "mean").}
}
\value{
data.frame of normalized expression values
\alias{mva.plot.pair}
\title{mva.plot.pair}
\usage{
-mva.plot.pair(array, title = F, small.positive = 0.1)
+mva.plot.pair(array, title = FALSE, small.positive = 0.1)
}
\arguments{
\item{array}{Array of data to plot}