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

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

View source: R/lowess.normalize.R

Description

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

Usage

1

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.

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)
  # 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,]
 

Example output

[1] 12488     7
               ID   c1   c2   c3     t1     t2     t3
1  AFFX-MurIL2_at 16.0 14.1 19.3 2782.7 2861.3 2540.2
2 AFFX-MurIL10_at 22.7  6.9 28.2   18.6   12.7    7.5
3  AFFX-MurIL4_at 33.9 17.1 23.9   24.9   25.2   24.9
               ID       c1       c2       c3        t1        t2        t3
1  AFFX-MurIL2_at 4.304733 4.076621 4.560498 11.442270 11.611246 11.385874
2 AFFX-MurIL10_at 4.809354 3.045594 5.107593  4.217231  3.795548  2.982039
3  AFFX-MurIL4_at 5.387947 4.354922 4.868908  4.638074  4.784143  4.713222

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