normalizeData

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

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").

normalization


  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).


DEXUS identifies differentially expressed genes in RNA-Seq
data under all possible study designs such as studies without
replicates, without sample groups, and with unknown conditions.
DEXUS works also for known conditions, for example for RNA-Seq
data with two or multiple conditions. RNA-Seq read count data
can be provided both by the S4 class Count Data Set and by read
count matrices. Differentially expressed transcripts can be
visualized by heatmaps, in which unknown conditions,
replicates, and samples groups are also indicated. This
software is fast since the core algorithm is written in C. For
very large data sets, a parallel version of DEXUS is provided
in this package. DEXUS is a statistical model that is selected
in a Bayesian framework by an EM algorithm. DEXUS does not need
replicates to detect differentially expressed transcripts,
since the replicates (or conditions) are estimated by the EM
method for each transcript. The method provides an
informative/non-informative value to extract differentially
expressed transcripts at a desired significance level or power.

Guenter Klambauer

dexus

DEXUS - Identifying Differential Expression in RNA-Seq Studies
with Unknown Conditions or without Replicates

normalizeData function

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).

normalizeData: Normalization of RNA-Seq count data.

Description

Usage

Arguments

Value

References

Examples