NormqPCR (version 1.18.0)

CqValues: Compute Cq value and amplification efficiency

Description

This function calculates Cq value and amplification efficiency for a CyclesSet. It is based on function pcrbatch of package qpcR.

Usage

CqValues(object, ...)
"CqValues"(object, Effmethod = "expfit", group = NULL,  model = l5, check = "uni2", checkPAR = parKOD(),  remove = "none", exclude = NULL, type = "cpD2",  labels = NULL, norm = FALSE, baseline = NULL,  basefac = 1, smooth = NULL,  smoothPAR = list(span = 0.1),  factor = 1, opt = FALSE,  optPAR = list(sig.level = 0.05, crit = "ftest"),  plot = FALSE, verbose = FALSE, ...)

Arguments

object

an object of class CyclesSet.

Effmethod

a character vector defining the methods for computing amplification efficiency.

group

a vector containing the grouping for possible replicates.

model

the model to be used for all runs. Default model is l5.

check

the method for kinetic outlier detection in KOD. Method "uni2" is set as default which is a test on sigmoidal structure.

checkPAR

parameters to be supplied to the check method. See parKOD.

remove

indicates which runs to be removed. Either none of them, those which failed to fit or from the outlier methods.

exclude

indicates samples to be excluded from calculation, either "" for samples with missing column names or a regular expression defining columns (samples); see 'Details' and 'Examples' in modlist.

type

the point on the amplification curve which is used for efficiency estimation; see efficiency.

labels

a vector containing labels which define replicate groups. See more details in pcrbatch and ratiobatch.

norm

a logical value which determines whether the raw data should be normalized within [0, 1] before model fitting or not.

baseline

type of baseline subtraction. More details in efficiency.

basefac

a factor when using averaged baseline cycles, such as 0.95.

smooth

the curve smoothing method. See more details in pcrbatch.

smoothPAR

parameters to be supplied to smoothing method in smooth.

factor

a multiplication factor for the fluorescence response values.

opt

a logical value which determines whether model selection should be applied to each model or not.

optPAR

parameters to be supplied for model selection in mselect.

plot

a logical value. If TRUE, the single runs are plotted from the internal modlist for diagnostics.

verbose

a logical value. If TRUE, fitting and tagging results will be displayed in the console.

...

other parameters to be passed to downstream methods.

Value

"qPCRBatch".

Details

Allows the user to compute Cq value and amplification efficiency. In addition, all values generated during the computations are saved. This function has four choices of methods for computing amplification efficiency values which are the methods provided by package qpcR. More details on technical replication and normalization is given in the vignette NormqPCR.

References

Perkins, JR, Dawes, JM, McMahon, SB, Bennett, DL, Orengo, C, Kohl, M (2012). ReadqPCR and NormqPCR: R packages for the reading, quality checking and normalisation of RT-qPCR quantification cycle (Cq) data. BMC Genomics, 13, 1:296.

See Also

pcrbatch, CyclesSet-class, qPCRBatch-class

Examples

  ## Read in the raw qPCR data from file "LC480_Example.txt"
  path <- system.file("exData", package = "ReadqPCR")
  LC480.example <- file.path(path, "LC480_Example.txt")
  cycData <- read.LC480(file = LC480.example)

  ## Read in the sample information data from file "LC480_Example_SampleInfo.txt". 
  LC480.SamInfo <- file.path(path, "LC480_Example_SampleInfo.txt")
  samInfo <- read.LC480SampleInfo(LC480.SamInfo)

  ## Merge information
  cycData1 <- merge(cycData, samInfo)

  ## Compute Cq values
  ## 1) use sigmoidal model
  res1 <- CqValues(cycData1, Effmethod = "sigfit")
  res1
  effs(res1)
  se.effs(res1)

  ## 2) fit exponential model (default)
  res2 <- CqValues(cycData1, Effmethod = "expfit")
  res2
  effs(res2)
  se.effs(res2)

  ## 3) use window of linearity
  res3 <- CqValues(cycData1, Effmethod = "sliwin")
  res3
  effs(res3)
  se.effs(res3)

  ## 4) linear regression of efficiency
  res4 <- CqValues(cycData1, Effmethod = "LRE")
  res4
  effs(res4)
  se.effs(res4)