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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