library(ggplot2) library(dplyr)
# Attach the DeLorean data frame to access members dl <- analyse.variance(dl, adjust.cell.sizes=FALSE) attach(dl)
This data set contains expression data, $x_{g,c}$, for
$G=r nrow(dl$expr)
$ genes and $C=r ncol(dl$expr)
$ cells.
The expression values are distributed as
stopifnot(ncol(expr) > 0) stopifnot(nrow(expr) > 0) qplot(as.vector(expr))
Meta data exists for r nrow(dl$cell.meta)
cells. These were captured at
r length(levels(cell.meta$capture))
distinct time points.
ggplot(cell.meta, aes(capture)) + geom_bar()
We have the following meta data for the cells:
summary(cell.meta)
Estimates of cell sizes by capture time are:
ggplot(cell.sizes %>% left_join(cell.meta), aes(x=capture, y=S.hat)) + geom_boxplot()
Boxplots of expression over capture time of some randomly sampled genes. The red lines show the mean expression at each capture time.
plot(dl, type="expr.data")
We have the following meta data for the genes:
summary(gene.meta)
# Detach the previously attached DeLorean data frame detach(dl)
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