selectHKs: Selection of reference/housekeeping genes

In NormqPCR: Functions for normalisation of RT-qPCR data

Description

This function can be used to determine a set of reference/housekeeping (HK) genes for gene expression experiments

Usage

selectHKs(qPCRBatch, ...)

## S4 method for signature 'matrix'
selectHKs(qPCRBatch, group, method = "geNorm", minNrHKs = 2, log = TRUE, Symbols, 
        trace = TRUE, na.rm = TRUE)

## S4 method for signature 'qPCRBatch'
selectHKs(qPCRBatch, group, method = "geNorm", minNrHKs = 2, log = TRUE, Symbols, 
	      trace = TRUE, na.rm = TRUE)

Arguments

qPCRBatch	matrix or qPCRBatch, containing the data (expression matrix) in the exprs slot
...	Extra arguments, detailed below
group	optional factor not used by all methods, hence may be missing
method	method to compute most stable genes
minNrHKs	minimum number of HK genes that should be considered
log	logical: is data on log-scale
Symbols	gene symbols
trace	logical, print additional information
na.rm	a logical value indicating whether NA values should be stripped before the computation proceeds.

Details

This function can be used to determine a set of reference/housekeeping (HK) genes for gene expression experiments. The default method "geNorm" was proposed by Vandesompele et al. (2002).

Currently, the geNorm method by Vandesompele et al. (2002) and the NormFinder method of Andersen et al. (2004) are implemented.

Vandesompele et al. (2002) propose a cut-off value of 0.15 for the pairwise variation. Below this value the inclusion of an additional housekeeping gene is not required.

Value

If method = "geNorm" a list with the following components is returned

ranking	ranking of genes from best to worst where the two most stable genes cannot be ranked
variation	pairwise variation during stepwise selection
meanM	average expression stability M

If method = "NormFinder" a list with the following components is returned

ranking	ranking of genes from best to worst where the two most stable genes cannot be ranked
rho	stability measure rho of Andersen et al. (2004)

Author(s)

Matthias Kohl [e-mail]

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.

Jo Vandesompele, Katleen De Preter, Filip Pattyn et al. (2002). Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biology 2002. 3(7):research0034.1-0034.11. http://genomebiology.com/2002/3/7/research/0034/

Claus Lindbjerg Andersen, Jens Ledet Jensen and Torben Falck Orntoft (2004). Normalization of Real-Time Quantitative Reverse Transcription-PCR Data: A Model-Based Variance Estimation Approach to Identify Genes Suited for Normalization, Applied to Bladder and Colon Cancer Data Sets. CANCER RESEARCH 64, 5245-5250, August 1, 2004. http://cancerres.aacrjournals.org/cgi/content/full/64/15/5245

Examples

  data(geNorm)
  tissue <- as.factor(c(rep("BM", 9), rep("FIB", 20), rep("LEU", 13),
                        rep("NB", 34), rep("POOL", 9)))
  res.BM <- selectHKs(geNorm.qPCRBatch[,tissue == "BM"], method = "geNorm", 
                      Symbols = featureNames(geNorm.qPCRBatch), minNrHK = 2, 
                      log = FALSE)

Example output

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, cbind, colMeans, colSums, colnames, 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 
###############################################################

Step 1:

stability values M:

    HPRT1     YWHAZ    RPL13A       UBC      GAPD      SDHA       TBP      HMBS 
0.5160313 0.5314564 0.5335963 0.5700961 0.6064919 0.6201470 0.6397969 0.7206013 
      B2M      ACTB 
0.7747634 0.8498739 
average stability M:	0.63628545246682

variable with lowest stability (largest M value):	ACTB

Pairwise variation, (9/10):	0.0764690052563778

###############################################################

Step 2:

stability values M:

    HPRT1    RPL13A     YWHAZ       UBC      GAPD      SDHA       TBP      HMBS 
0.4705664 0.5141375 0.5271169 0.5554718 0.5575295 0.5738460 0.6042110 0.6759176 
      B2M 
0.7671985 
average stability M:	0.582888329316757

variable with lowest stability (largest M value):	B2M

Pairwise variation, (8/9):	0.0776534266912183

###############################################################

Step 3:

stability values M:

    HPRT1    RPL13A      SDHA     YWHAZ       UBC      GAPD       TBP      HMBS 
0.4391222 0.4733732 0.5243665 0.5253471 0.5403137 0.5560120 0.5622094 0.6210820 
average stability M:	0.530228279613623

variable with lowest stability (largest M value):	HMBS

Pairwise variation, (7/8):	0.0671119963410967

###############################################################

Step 4:

stability values M:

    HPRT1    RPL13A     YWHAZ       UBC      SDHA      GAPD       TBP 
0.4389069 0.4696398 0.4879728 0.5043292 0.5178634 0.5245346 0.5563591 
average stability M:	0.499943693933222

variable with lowest stability (largest M value):	TBP

Pairwise variation, (6/7):	0.0681320232188603

###############################################################

Step 5:

stability values M:

    HPRT1    RPL13A       UBC     YWHAZ      GAPD      SDHA 
0.4292808 0.4447874 0.4594181 0.4728920 0.5012107 0.5566762 
average stability M:	0.477377523800525

variable with lowest stability (largest M value):	SDHA

Pairwise variation, (5/6):	0.0806194432580746

###############################################################

Step 6:

stability values M:

      UBC    RPL13A     HPRT1     YWHAZ      GAPD 
0.4195958 0.4204997 0.4219179 0.4424631 0.4841646 
average stability M:	0.437728198765878

variable with lowest stability (largest M value):	GAPD

Pairwise variation, (4/5):	0.0841653121631615

###############################################################

Step 7:

stability values M:

   RPL13A       UBC     YWHAZ     HPRT1 
0.3699163 0.3978736 0.4173706 0.4419220 
average stability M:	0.406770625156432

variable with lowest stability (largest M value):	HPRT1

Pairwise variation, (3/4):	0.097678269387021

###############################################################

Step 8:

stability values M:

      UBC    RPL13A     YWHAZ 
0.3559286 0.3761358 0.3827933 
average stability M:	0.371619241507029

variable with lowest stability (largest M value):	YWHAZ

Pairwise variation, (2/3):	0.113745049966055

###############################################################

Step 9:

stability values M:

   RPL13A       UBC 
0.3492712 0.3492712 
average stability M:	0.349271187472188

NormqPCR documentation built on Nov. 8, 2020, 6:37 p.m.