deltaDeltaCt: Perform normalization and differential expression with given...
In NormqPCR: Functions for normalisation of RT-qPCR data

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

Normalise qPCRBatch RT-qPCR data using housekeeping genes as control, then perform differential expression analysis using the delta delta Cq method.

  deltaDeltaCt(qPCRBatch,...)
  ## S4 method for signature 'qPCRBatch'
deltaDeltaCt(qPCRBatch, maxNACase=0, maxNAControl=0, hkgs, contrastM, 
             case, control, paired=TRUE, hkgCalc="arith", statCalc="arith")
  deltaDeltaCq(qPCRBatch, maxNACase=0, maxNAControl=0, hkgs, contrastM,
             case, control, paired=TRUE, hkgCalc="arith", statCalc="arith")

`qPCRBatch`	qPCR-specific expression set, containing qPCR data.
`...`	Extra arguments, detailed below
`maxNACase`	Maximum number of NA values allowed before a detector's reading is discarded for samples designated as case.
`maxNAControl`	Maximum number of NA values allowed before a detector's reading is discarded for samples designated as control.
`hkgs`	String containing the name of th name of the housekeeping gene which will be used to normalise the rest of the genes.
`contrastM`	A binary matrix which designates case and control samples.
`case`	The name of the column in contrastM that corresponds to the case samples.
`control`	The name of the column in contrastM that corresponds to the control samples.
`paired`	Logical - if TRUE the detectors and housekeepers in the same sample will be paired for calculating standard deviation, effectively meaning we will be calculating standard deviation of the differences. If FALSE, there will be no pairing, and standard deviation will be pooled between the detector and housekeepers.
`hkgCalc`	String - either "arith" or "geom", details how the different housekeeper genes should be combined - either by using the arithmetic or geometric mean.
`statCalc`	String - either "arith" or "geom", details how genes should be combined - either by using the arithmetic or geometric mean.

Takes expression set of qPCR values and normalises them using different housekeeping genes. Returns seperate sets of values for each housekeeping gene given.

matrix with columns containing the detector ids, 2^delta Cq values for the sample of interest and the callibrator sample, alongside their respective standard deviations, the 2^delta delta Cq values and the minimum and maximum values (ie the values that are 1 sd away )

James Perkins jimrperkins@gmail.com

Kenneth Livak, Thomase Schmittgen (2001). Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2^DDCt Method. Methods 25, 402-408, 2001 http://www.ncbi.nlm.nih.gov/pubmed/11846609

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.

selectHKs, deltaCq

  path <- system.file("exData", package = "NormqPCR")
  taqman.example <- file.path(path, "example.txt")
  qPCRBatch.taqman <- read.taqman(taqman.example)
  hkg <- "Actb-Rn00667869_m1"

  contM <- cbind(c(0,0,1,1,0,0,1,1),c(1,1,0,0,1,1,0,0))
  colnames(contM) <- c("interestingPhenotype","wildTypePhenotype")
  rownames(contM) <- sampleNames(qPCRBatch.taqman)

  ddCq.taqman <- deltaDeltaCq(qPCRBatch = qPCRBatch.taqman, maxNACase=1, 
                              maxNAControl=1, hkg=hkg, contrastM=contM, 
                              case="interestingPhenotype", 
                              control="wildTypePhenotype", 
                              statCalc="geom", hkgCalc="arith")
  head(ddCq.taqman)

Loading required package: RColorBrewer
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, basename, cbind, colMeans, colSums, colnames,
    dirname, do.call, duplicated, eval, evalq, get, grep, grepl,
    intersect, is.unsorted, lapply, lengths, mapply, match, mget,
    order, paste, pmax, pmax.int, pmin, pmin.int, rank, rbind,
    rowMeans, rowSums, rownames, sapply, setdiff, sort, table, tapply,
    union, unique, unsplit, which, which.max, which.min

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: ReadqPCR
Loading required package: affy
Loading required package: qpcR
Loading required package: MASS
Loading required package: minpack.lm
Loading required package: rgl
Loading required package: robustbase

Attaching package: 'robustbase'

The following object is masked from 'package:Biobase':

    rowMedians

Loading required package: Matrix
Warning messages:
1: In read.dcf(con) :
  URL 'http://bioconductor.org/BiocInstaller.dcf': status was 'Couldn't resolve host name'
2: In rgl.init(initValue, onlyNULL) : RGL: unable to open X11 display
3: 'rgl_init' failed, running with rgl.useNULL = TRUE 
4: .onUnload failed in unloadNamespace() for 'rgl', details:
  call: fun(...)
  error: object 'rgl_quit' not found 
Warning message:
In read.taqman(taqman.example) :
  Incompatible phenoData object. Created a new one using sample name data derived from raw data.

There were 12 warnings (use warnings() to see them)
                    ID 2^-dCt.interestingPhenotype interestingPhenotype.sd
1   Actb.Rn00667869_m1                   1.000e+00               0.000e+00
2 Adipoq.Rn00595250_m1                   1.587e-01               2.280e-02
3 Adrbk1.Rn00562822_m1                   2.602e-02               3.266e-02
4 Agtrl1.Rn00580252_s1                   2.300e-02               1.014e-02
5   Alpl.Rn00564931_m1                   1.892e-04               4.770e-05
6    B2m.Rn00560865_m1                   2.464e-01               2.498e-02
  2^-dCt.wildTypePhenotype wildTypePhenotype.sd              2^-ddCt
1                1.000e+00            0.000e+00 1                   
2                1.171e+00            2.131e-01 0.135541545192243   
3                       NA                   NA +                   
4                3.434e-02            8.584e-03 0.669721905042939   
5                2.298e-04            6.107e-05 0.823327272466571   
6                5.965e-01            7.668e-02 0.413128242070071   
  2^-ddCt.min 2^-ddCt.max
1          NA          NA
2          NA          NA
3          NA          NA
4          NA          NA
5          NA          NA
6          NA          NA