plot.qq: Histogram and Normal Quantile-Quantile plot

In gnyamundanda/sma: Statistical Microarray Analysis

Description

Produces a histogram and a normal Quantile-Quantile plot of the data. The points corresponding to genes with statistics less/greater than a user defined threshold are highlighted. The histogram and Q-Q plots are displayed on the same page.

Usage

plot.qq(x, name, low=-5, high=5,...)

Arguments

x	a numeric vector containing the statistics whose histogram and Q-Q plot will be produced. Missing values (NAs) are allowed.
name	title for the plots.
low	lower threshold: points with statistic < low are colored in green.
high	upper threshold: points with statistic > high are colored in red.
...	additional graphical parameters

Author(s)

Sandrine Dudoit, [e-mail]
Yee Hwa Yang, [e-mail]

References

Chambers, J. M., Cleveland, W. S., Kleiner, B. and Tukey, P. A. (1983). Graphical Methods for Data Analysis. Wadsworth, Belmont, California.

Hoaglin, D. C., Mosteller, F. and Tukey, J. W., editors (1983). Understanding Robust and Exploratory Data Analysis. Wiley, New York.

See Also

plot.spatial, plot.t2, stat.t2, hist, qqnorm.

Examples

data(MouseArray)
## mouse.setup <- init.grid()
## mouse.data <- init.data() ## see \emph{init.data}
## mouse.lratio <- stat.ma(mouse.data, mouse.setup)

## Calculation of t-statistics
## cl <- c(rep(1,3), rep(2,3))
## mouse.t2 <- stat.t2(mouse.lratio, cl)

## Diagnostic plots
plot.qq(mouse.t2$t, "Mouse")

gnyamundanda/sma documentation built on May 3, 2019, 5:17 p.m.