qpcrBatch
object.
We have adapted this algorithm from the function normalize.invariantset
from the affy package.
normQpcrRankInvariant(qBatch, refType, rem.highCt = FALSE, thresh.Ct = 30)
qpcrBatch
object. rem.highCt
= FALSE,
genes with Ct values > thresh.Ct are removed from the data set. qpcrBatch
object, the normalized
slot is now set at TRUE.
The names of the rank-invariant genes used for normalization are stored as a vector in the normGenes
slot of the qpcrBatch
object returned.
To retrieve the rank-invariant gene names, use qpcrBatch@normGenes
.
qpcrBatch
object is paired against a reference. There are several ways to specify
what a sensible choice for the reference sample should be.
1. The reference is an experimental sample in the qpcrBatch
object.
Specify refType
as an integer
value, corresponding to the index of which experimental sample is the reference.
2. The reference is the sample which is closest to mean of all the experiments.
Specify refType = "mean"
.
3. The reference is the sample which is closest to median of all the experiments.
Specify refType = "median"
.
4. The reference is the mean of all experiments in the qpcrBatch
object.
Specify refType = "pseudo.mean"
.
5. The reference is the median of all experiments in the qpcrBatch
object.
Specify refType = "pseudo.median"
.
normQpcrQuantile
, normalize.invariantset
data(qpcrBatch.object)
mynormRI.data <- normQpcrRankInvariant(qpcrBatch.object, 1)
mynormRI.data@normGenes # retrieves names of genes in the rank-invariant set
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