normQpcrRankInvariant: Function for Rank-Invariant Set Normalization for qPCR Data.
In qpcrNorm: Data-driven normalization strategies for high-throughput qPCR data.

Description Usage Arguments Details Value Author(s) See Also Examples

Implements rank-invariant set normalization for a qpcrBatch object. We have adapted this algorithm from the function normalize.invariantset from the affy package.

1	normQpcrRankInvariant(qBatch, refType, rem.highCt = FALSE, thresh.Ct = 30)

`qBatch`	A `qpcrBatch` object.
`refType`	Indicates what reference sample should be used, can be an integer or character string. See Details below.
`rem.highCt`	Logical indicator, TRUE if user wishes to remove genes with high Ct values (very low expression) that may be associated poor data quality.
`thresh.Ct`	Numerical value indicating the Ct value cutoff threshold, if `rem.highCt` = FALSE, genes with Ct values > thresh.Ct are removed from the data set.

The algorithm computes all rank-invariant sets of genes between pairwise comparisons where each experimental sample in the 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".

A 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.

Jess Mar jess@jimmy.harvard.edu

normQpcrQuantile, normalize.invariantset

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 data(qpcrBatch.object)
 mynormRI.data <- normQpcrRankInvariant(qpcrBatch.object, 1) 
 mynormRI.data@normGenes		# retrieves names of genes in the rank-invariant set