LPE (version 1.46.0)

lowess.normalize: lowess normalization of the data (based on M vs A graph)

Description

All the chips are normalized w.r.t. 1st chip

Usage

lowess.normalize(x,y)

Arguments

x

x is the chip data w.r.t. which other chips would be normalized

y

y is the chip data which would be normalized

Value

Returns the lowess normalized chip intensity.

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

  library(LPE)
  # Loading the LPE library
 
  data(Ley)
  # Loading the data set
  dim(Ley) #gives 12488 * 7
  Ley[1:3,]

  Ley[1:1000,2:7] <- preprocess(Ley[1:1000,2:7],data.type="MAS5")
  Ley[1:3,]