changeCtLayout {HTqPCR} | R Documentation |
A function for splitting up the individual qPCR cards, in case there are multiple samples present on each card. I.e. for cases where the layout isn't 1 sample x 384 features, but for example 4 samples x 96 features on each 384 well card.
changeCtLayout(q, sample.order)
q |
a qPCRset object. |
sample.order |
vector, same length as number of features on each card (e.g. 384). See details. |
The result from each qPCR run of a given card typically gets presented together, such as in a file with 384 lines, one per feature, for 384 well plates. However, some cards may contain multiple samples, such as commercial cards that are designed to be loaded with two separate samples and then include 192 individual features.
Per default, each card is read into the qPCRset
object as consisting of a single sample, and hence one column in the Ct data matrix. When this is not the case, the data can subsequently be split into the correct features x samples (rows x columns) dimensions using this function. The parameter sample.order
is a vector, that for each feature in the qPCRset
indicates what sample it actually belongs to.
In the new qPCRset
the samples (Ct columns) are ordered first by sample.order
then by the original sampleNames
, as shown in the examples below.
A qPCRset object like the input, but with the dimensions changed according to the new layout.
Since the actual biological samples are likely to differ on each card, after applying changeCtLayout
renaming of the samples in qPCRset
using sampleNames
is advisable.
The features are assumed to be identical for all samples on a given card! I.e. if for example sample.order=rep(c("A", "B"), each=192)
, then feature number 1 (the first for sample A) should be the same as feature number 193 (the first for sample B). The new featureNames
are taken for those features listed as belonging to the first sample in sample.order
.
Heidi Dvinge
# Example data data(qPCRraw) # With e.g. 2 or 4 samples per 384 well card. sample2.order <- rep(c("subSampleA", "subSampleB"), each=192) sample4.order <- rep(c("subA", "subB", "subC", "subD"), each=96) # Splitting the data into all individual samples qPCRnew2 <- changeCtLayout(qPCRraw, sample.order=sample2.order) show(qPCRnew2) qPCRnew4 <- changeCtLayout(qPCRraw, sample.order=sample4.order) show(qPCRnew4) sampleNames(qPCRnew4)