preprocess {LPE} | R Documentation |

## Preprocessing the data (IQR normalization, thresholding, log-
transformation, and lowess normalization)

### Description

Finds inter-quartile range of the data = (75th percentile - 25th percentile),
thresholds low intensity MAS4, MAS5 and dChip data to 1, then log transforms
the data (base 2), and dows lowess normalization

### Usage

preprocess(x, data.type="MAS5",threshold=1,LOWESS=TRUE)

### Arguments

`x` |
x is the data-set which needs preprocessing. |

`data.type` |
Three types of data accepted in the current version :
MAS4 (Microarray suite software) , MAS5 and dChip |

`threshold` |
threshold is the 'thresholding value' below which
all data would be thresholded (default = 1). |

`LOWESS` |
LOWESS is a logical variable which determines if lowess
normalization needs to be performed. |

### Value

Returns a data-set of same dimensions as that of the input data. It has
IQR normalization for MAS4 and MAS5 data. Low intensities of MAS4, MAS5
and dChip data are thresholded to 1. Then data is transformed to base 2, and
finally lowess based normalization is applied.

### 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.

### 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",
threshold=1, LOWESS=TRUE)
Ley[1:3,]

[Package

*LPE* version 1.1.5

Index]