normalize: Normalization of data

In NBBttest: Negative Binomial Beta t-Test

Normalization of data

Description

Function normalize makes all libraries in dataset have the same library size.

Usage

normalized(dat, nci, m=0, lg2="no")

Arguments

dat	count data of RNA reads.
nci	number of columns for the information of genes or isoforms in dataset.
m	numeric value for choosing genes or isoforms. If user wants to discard genes or isoforms with mean < 5, then m = 5. The default value is 0.
lg2	logistic value. lg2="yes"indicates that data are transformed in logarithm of 2.

Details

Due to difference in RNA abstraction between libraries or cell samples or tissues, PCR amounts of RNA libraries would have difference that is not due to biological effects. To correctly compare differential expressisons of genes between conditions or samples, one must should give the same RNA abstraction in all given samples. This is impossible. To address this problem, only one way is to normalize these count data across all given samples so that all experimental samples (libraries) have the same total counts.

Value

output a standard datasheet.

Author(s)

Yuan-De Tan [e-mail]

References

Yuan-De Tan Anita M. Chandler, Arindam Chaudhury, and Joel R. Neilson(2015) A Powerful Statistical Approach for Large-scale Differential Transcription Analysis. Plos One, 10.1371/journal.pone.0123658.
Anders S, Huber W (2010) Differential expression analysis for sequence count data. Genome Biol, 11: R106.

Examples

data(jkttcell)	
njkttcell<-normalized(dat=jkttcell[1:50,],nci=7)

NBBttest documentation built on May 30, 2022, 1:05 a.m.