quan.norm: Finding quartile range

In LPE: Methods for analyzing microarray data using Local Pooled Error (LPE) method

Description

Finds quartile range of the data (default is IQR = 75th percentile - 25th percentile).

Usage

  quan.norm(x, percent=50)

Arguments

x	x is a vector for which quartile range has to be found.
percent	Percentage for which quartile range is needed

Value

Returns a numeric value representing the difference of 75th percentile and 25th percentile of the vector. It is used for normalization across the chips - basic assumption is that net differential expression of the middle half of the genes in microarray experiment is zero, which is conservative assumption as typically only 5-10 differential expression.

Author(s)

Nitin [e-mail]

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
 
  quan.norm(1:5) 
  

LPE documentation built on Nov. 8, 2020, 5:25 p.m.