normalizeData {dexus} | R 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")

[Package dexus version 1.26.0 Index]