print.TC {acde} | R Documentation |
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.
## S3 method for class 'TC' print(x, ...) ## S3 method for class 'TC' summary(object, ...)
x |
an object of class ' |
object |
an object of class ' |
... |
further arguments passed to or from other methods. |
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.
## 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)