normaliseIllumina {beadarray} | R Documentation |
Normalises expression intensities from an ExpressionSetIllumina
object so that the intensities are comparable between arrays.
normaliseIllumina(BSData, method="quantile", transform="none", T=NULL, ...)
BSData |
an ExpressionSetIllumina object |
method |
character string specifying normalisation method
(options are "quantile" , "qspline" , "vsn" ,
"rankInvariant" , "median" and "none" . |
transform |
character string specifying transformation to apply
to the data prior to normalisation (options are "none" ,
"log2" and "vst" |
T |
A target distribution vector used when method="rankInvariant"
normalisation. If NULL , the mean is used. |
... |
further arguments to be passed to lumiT |
Normalisation is intended to remove from the expression measures any systematic trends which arise from the microarray technology rather than from differences between the probes or between the target RNA samples hybridized to the arrays.
In this function, the transform
specified by the user is
applied prior to the chosen normalisation procedure.
When transform="vst"
the variance-stabilising transformation
from the 'lumi' package is applied to the data.
Refer to the lumiT
documentation for further particulars. Note that
the Detection P values are only passed on when they are available
(i.e. not NA)
For further particulars on the different normalisation methods options
refer to the individual help pages (?normalize.quantiles
for
"quantile"
, ?normalize.qspline
for "qspline",
?rankInvariantNormalise
for "rankInvariant"
,
?medianNormalise
for "median"
and ?vsn2
for "vsn"
.
For median normalisation, the intensity for each gene is adjusted by subtracting the median of all genes on the array and then adding the median across all arrays. The effect is that each array then has the same median value.
Note: If your BSData
object contains data already on the
log-scale, be careful that you choose an appropriate transform
to avoid transforming it twice. The same applies for the "vst"
transformation and "vsn"
normalisation methods which require
the expression data stored in BSData
to be on the original
(un-logged) scale. When method="vsn"
, transform must be set to
"none"
, since this method transforms and normalises the data as
part of the model.
An 'ExpressionSetIllumina' object which conatains the transformed and normalised expression values for each array.
Matt Ritchie
data(BSData) BSData.norm = normaliseIllumina(BSData, method="quantile", transform="log2")