Stemmed Heat Diagram
Creates a heat diagram showing the co-regulation of genes under one condition with a range of other conditions.
heatDiagram(results, coef, primary=1, names=NULL, treatments=colnames(coef), limit=NULL,
orientation="landscape", low="green", high="red", cex=1, mar=NULL,
ncolors=123, ...)
heatdiagram(stat, coef, primary=1, names=NULL, treatments=colnames(stat),
critical.primary=4, critical.other=3, limit=NULL, orientation="landscape",
low="green", high="red", cex=1, mar=NULL, ncolors=123, ...)results |
|
stat |
numeric matrix of test statistics. Rows correspond to genes and columns to treatments or contrasts between treatments. |
coef |
numeric matrix of the same size as |
primary |
number or name of the column to be compared to the others. Genes are included in the diagram according to this column of |
names |
optional character vector of gene names |
treatments |
optional character vector of treatment names |
critical.primary |
critical value above which the test statistics for the primary column are considered significant and included in the plot |
critical.other |
critical value above which the other test statistics are considered significant. Should usually be no larger than |
limit |
optional value for |
orientation |
|
low |
color associated with repressed gene regulation |
high |
color associated with induced gene regulation |
ncolors |
number of distinct colors used for each of up and down regulation |
cex |
factor to increase or decrease size of column and row text |
mar |
numeric vector of length four giving the size of the margin widths.
Default is |
... |
any other arguments will be passed to the |
Users are encouraged to use heatDiagram rather than heatdiagram as the later function may be removed in future versions of limma.
This function plots an image of gene expression profiles in which rows (or columns for portrait orientation) correspond to treatment conditions and columns (or rows) correspond to genes. Only genes which are significantly differentially expressed in the primary condition are included. Genes are sorted by differential expression under the primary condition.
Note: the plot produced by this function is unique to the limma package. It should not be confused with "heatmaps" often used to display results from cluster analyses.
An image is created on the current graphics device. A matrix with named rows containing the coefficients used in the plot is also invisibly returned.
Gordon Smyth
## Not run: MA <- normalizeWithinArrays(RG) design <- cbind(c(1,1,1,0,0,0),c(0,0,0,1,1,1)) fit <- lmFit(MA,design=design) contrasts.mouse <- cbind(Control=c(1,0),Mutant=c(0,1),Difference=c(-1,1)) fit <- eBayes(contrasts.fit(fit,contrasts=contrasts.mouse)) results <- decideTests(fit,method="global",p=0.1) heatDiagram(results,fit$coef,primary="Difference") ## End(Not run)
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