Last data update: 2014.03.03

R: Normalization of RNA-Seq count data.
normalizeDataR Documentation

Normalization of RNA-Seq count data.

Description

Normalizes RNA-seq count data using previously published approaches. Each samples' read counts are corrected by a normalizing factor. The options are "RLE" by (Anders and Huber, 2010), and "upperquartile" by (Bullard et al., 2010).

Usage

  normalizeData(X, normalization)

Arguments

X

data a raw data matrix, where' columns are interpreted as samples and rows as genomic regions.

normalization

method used for normalizing the reads. RLE is the method used by (Anders and Huber, 2010), upperquartile is the Upper-Quartile method from (Bullard et al., 2010), and none deactivates normalization. (Default = "RLE").

Value

"list" A list containing the normalized data (in its "X" component) as well as the size-factors used for the normalization ("sizeFactors").

Author(s)

Guenter Klambauer klambauer@bioinf.jku.at and Thomas Unterthiner unterthiner@bioinf.jku.at

References

Anders, S. and Huber, W. (2010). Differential expression analysis for sequence count data. Genome Biol, 11(10), R106.

Bullard, J. H., Purdom, E., Hansen, K. D., and Dudoit, S. (2010). Evaluation of statistical methods for normalization and differential expression in mRNA-seq experiments. BMC Bioinformatics, 11, 94.

Examples

data(dexus)
norm <- normalizeData(countsBottomly,"RLE")

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(dexus)
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, xtabs

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

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, 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, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit


Attaching package: 'dexus'

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

    sizeFactors

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/dexus/normalizeData.Rd_%03d_medium.png", width=480, height=480)
> ### Name: normalizeData
> ### Title: Normalization of RNA-Seq count data.
> ### Aliases: normalizeData
> 
> ### ** Examples
> 
> data(dexus)
> norm <- normalizeData(countsBottomly,"RLE")
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>