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OLIN (version 1.50.0)

anovaint: One-factorial ANOVA assessing intensity-dependent bias

Description

This function performs an one-factorial analysis of variance assessing intensity-dependent bias for a single array. The predictor variable is the average logged intensity of both channels and the response variable is the logged fold-change.

Usage

anovaint(obj,index,N=10)

Arguments

obj
object of class “marrayRaw” or “marrayNorm”
index
index of array to be tested
N
number of (intensity) levels for ANOVA

Value

summary.lm. For example, the squared multiple correlation coefficient $R-square$ equals the proportion of the variation of M that can be explained by the variation of A (based on the chosen ANOVA model.)

Details

The function anovaint performs a one-factorial ANOVA for objects of class “marrayRaw” or “marrayNorm”. The predictor variable is the average logged intensity of both channels A=0.5*(log2(Ch1)+log2(Ch2)). Ch1,Ch2 are the fluorescence intensities of channel 1 and channel 2, respectively. The response variable is the logged fold-change M=(log2(Ch2)-log2(Ch1)). The A-scale is divided in N intervals generating N levels of factor A. Note that N should divide the total number of spots approx. equally. The null hypothesis is the equality of mean(M) of the different levels (intervals). The model formula used is $M ~ (A - 1)$ (without an intercept term).

See Also

anova, summary.lm, anovaspatial, marrayRaw, marrayNorm

Examples

Run this code

# CHECK RAW DATA FOR INTENSITY-DEPENDENT BIAS
data(sw)
print(anovaint(sw,index=1,N=10))


# CHECK  DATA NORMALISED BY OLIN FOR INTENSITY-DEPENDENT BIAS
data(sw.olin)
print(anovaint(sw.olin,index=1,N=10))



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