Norm.qt: Normalize 2D Gel Volume data using Quantiles Normalization

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


This function allows to normalize 2D Gel Volume data using the Quantiles Normalization.


Norm.qt(data, n1, n2, plot = T)



a dataframe of raw 2D Gel Volume data. data should be raw intensities displayed with gel as columns with the name of columns corresponding to the names of the gels and spots as rows with the names of the rows corresponding to the name of the spots. The replicates for each condition should be ordered in following columns.


an integer. Number of replicates in condition 1.


an integer. Number of replicates in condition 2.


logical. if TRUE (default) displaying two RIplot, one with the raw data, another with normalized data.


2D Gel Volume data must be normalized in order to remove systemic variation prior to data analysis. The principle of the "quantiles normalization" is to set each quantile of each column (i.e. the spots volume data of each gels) to the mean of that quantile across gels. The intention is to make all the normalized columns have the same empirical distribution.This function is based on normalizeQuantiles from limma package.


The function returns a matrix of log2 transformed quantiles normalized data


Sebastien Artigaud


Artigaud, S., Gauthier, O. & Pichereau, V. (2013) "Identifying differentially expressed proteins in two-dimensional electrophoresis experiments: inputs from transcriptomics statistical tools." Bioinformatics, vol.29 (21): 2729-2734.

See Also




pecten.norm <- Norm.qt(pecten, n1=6, n2=6, plot=TRUE)

Example output

Loading required package: fdrtool
Loading required package: st
Loading required package: sda
Loading required package: entropy
Loading required package: corpcor
Loading required package: samr
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,, basename, cbind, colMeans, colSums, colnames,
    dirname,, duplicated, eval, evalq, get, grep, grepl,
    intersect, is.unsorted, lapply, lengths, mapply, match, mget,
    order, paste, pmax,, pmin,, 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: limma

Attaching package: 'limma'

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


Loading required package: Mulcom
Loading required package: fields
Loading required package: spam
Loading required package: dotCall64
Loading required package: grid
Spam version 2.2-2 (2019-03-07) is loaded.
Type 'help( Spam)' or 'demo( spam)' for a short introduction 
and overview of this package.
Help for individual functions is also obtained by adding the
suffix '.spam' to the function name, e.g. 'help( chol.spam)'.

Attaching package: 'spam'

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

    backsolve, forwardsolve

Loading required package: maps
See for
 an extensive vignette, other supplements and source code 
Loading required package: impute
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Loading required package: qvalue

prot2D documentation built on May 1, 2019, 11:54 p.m.