quartile.normalize: Normalization based on quartile range

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

View source: R/quartile.normalize.R

Description

Does Normalization based on quartile range

Usage

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  quartile.normalize(x, percent=50)

Arguments

x

x is a matrix or data.frame on which normalization has to be performed.

percent

Percentage for which normalization is needed

Value

Returns the normalized data based on quartile normalization

Author(s)

Nitin Jain[email protected]

References

J.K. Lee and M.O.Connell(2003). An S-Plus library for the analysis of differential expression. In The Analysis of Gene Expression Data: Methods and Software. Edited by G. Parmigiani, ES Garrett, RA Irizarry ad SL Zegar. Springer, NewYork.

Jain et. al. (2003) Local pooled error test for identifying differentially expressed genes with a small number of replicated microarrays, Bioinformatics, 1945-1951.

Jain et. al. (2005) Rank-invariant resampling based estimation of false discovery rate for analysis of small sample microarray data, BMC Bioinformatics, Vol 6, 187.

See Also

lpe

Examples

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  library(LPE)
  # Loading the LPE library

  data(Ley) 
 
 dim(Ley)
 # Gives 12488*7
 # First column is ID.

  subset <- 1:1000
  Ley[subset,2:7] <- quartile.normalize(Ley[subset,2:7],percent=50)

LPE documentation built on May 2, 2018, 2:51 a.m.