Zscore: Z-scores for identifying differential expression

In genArise: Microarray Analysis tool

Description

This function identify differential expressed genes by calculating an intensity-dependent Z-score. This function use a sliding window to calculate the mean and standard deviation within a window surrounding each data point, and define a Z-score where Z measures the number of standard deviations a data point is from the mean.

Usage

Zscore(spot.object,type,window.size)

Arguments

spot.object	A spot object
type	Type of analysis: "ri" is for a R-I analysis and "ma" is for M-A analysis
window.size	Size of the sliding window

Value

A dataSet object with attributes Cy3, Cy5, Id, Z-score.

Examples

data(Simon)
# Background Correction
c.spot <- bg.correct(Simon)
#Normalized data
n.spot <- grid.norm(c.spot,23,24)
#Filter spot
f.spot <- filter.spot(n.spot)
#Replicate filtering
u.spot <- spotUnique(f.spot)
#Zscore analysis
s.spot <- Zscore(u.spot)

Example output

Loading required package: locfit
locfit 1.5-9.1 	 2013-03-22
Loading required package: tkrplot
Loading required package: tcltk

Attaching package: 'genArise'

The following object is masked from 'package:utils':

    help

Warning messages:
1: no DISPLAY variable so Tk is not available 
2: loading Rplot failed 

genArise documentation built on Nov. 8, 2020, 6:29 p.m.