print.TC: Print Method for Time Course Analysis

In acde: Artificial Components Detection of Differentially Expressed Genes

Description

methods for the print and summary generics that print relevant results when performing a Time Course Analysis for detecting differentially expressed genes in gene expression data.

Usage

## S3 method for class 'TC'
print(x, ...)

## S3 method for class 'TC'
summary(object, ...)

Arguments

x	an object of class 'TC' as returned by function tc.
object	an object of class 'TC' as returned by function tc.
...	further arguments passed to or from other methods.

Details

With print, at each time point, if the desired FDR level was achieved (i.e. x$astar <= x$alpha), the results are printed for the differentially expressed genes and 10 more rows only. If the desired FDR level was not achieved, only ten rows are displayed.

summary prints a more concise version of the results.

See Also

tc, plot.TC.

Examples

## Time course analysis for 500 genes with 10 treatment 
## replicates and 10 control replicates
tPts <- c("h0", "12h", "24h")
n <- 500; p <- 20; p1 <- 10
Z <- vector("list", 3)
des <- vector("list", 3)
for(tp in 1:3){ des[[tp]] <- c(rep(1, p1), rep(2, (p-p1))) }
mu <- as.matrix(rexp(n, rate=1))
### h0 time point (no diff. expr.)
Z[[1]] <- t(apply(mu, 1, function(mui) rnorm(p, mean=mui, sd=1)))
### h12 time point (diff. expr. begins)
Z[[2]] <- t(apply(mu, 1, function(mui) rnorm(p, mean=mui, sd=1)))
#### Up regulated genes
Z[[2]][1:5,1:p1] <- Z[[2]][1:5,1:p1] + 
    matrix(runif(5*p1, 1, 3), nrow=5)
#### Down regulated genes
Z[[2]][6:15,(p1+1):p] <- Z[[2]][6:15,(p1+1):p] + 
    matrix(runif(10*(p-p1), 1, 2), nrow=10)
### h24 time point (maximum differential expression)
Z[[3]] <- t(apply(mu, 1, function(mui) rnorm(p, mean=mui, sd=1)))
#### 5 up regulated genes
Z[[3]][1:5,1:p1] <- Z[[3]][1:5,1:p1] + 5
#### 10 down regulated genes
Z[[3]][6:15,(p1+1):p] <- Z[[3]][6:15,(p1+1):p] + 4

resTC <- tc(Z, des)
resTC
summary(resTC)
plot(resTC)

## Not run: 
## Phytophthora Infestans Time Course Analysis (takes time...)
dataPI <- phytophthora
desPI <- vector("list", 4)
for(tp in 1:4){ desPI[[tp]] <- c(rep(1, 8), rep(2, 8)) }
resPI <- tc(dataPI, desPI)
resPI
summary(resPI)
plot(resPI)

## End(Not run)

acde documentation built on Nov. 8, 2020, 11:10 p.m.