1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
|
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/calculateFPKM.R
\name{calculateFPKM}
\alias{calculateFPKM}
\title{Calculate FPKMs}
\usage{
calculateFPKM(x, lengths, ..., subset.row = NULL, subset_row = NULL)
}
\arguments{
\item{x}{A numeric matrix of counts where features are rows and cells are columns.
Alternatively, a \linkS4class{SummarizedExperiment} or a \linkS4class{SingleCellExperiment} containing such counts.}
\item{lengths}{Numeric vector providing the effective length for each feature in \code{x}.}
\item{...}{Further arguments to pass to \code{\link{calculateCPM}}.}
\item{subset.row}{A vector specifying the subset of rows of \code{x} for which to return a result.}
\item{subset_row}{Soft-deprecated equivalent to the argument above.}
}
\value{
A numeric matrix of FPKM values with the same dimensions as \code{x} (unless \code{subset.row} is specified).
}
\description{
Calculate fragments per kilobase of exon per million reads mapped (FPKM) values from the feature-level counts.
}
\details{
FPKMs are computed by dividing the CPMs by the effective length of each gene in kilobases.
For RNA-seq datasets, the effective length is best set to the sum of lengths of all exons;
for nucleus sequencing datasets, the effective length may instead be the entire width of the gene body.
}
\examples{
example_sce <- mockSCE()
eff_len <- runif(nrow(example_sce), 500, 2000)
fout <- calculateFPKM(example_sce, eff_len)
str(fout)
}
\seealso{
\code{\link{calculateCPM}}, for the initial calculation of CPM values.
}
\author{
Aaron Lun, based on code by Davis McCarthy
}
|
