ggplot2_marginPlot: Plot percent increase in detection of DE genes across...
In ERSSA: Empirical RNA-seq Sample Size Analysis

Description Usage Arguments Details Value Author(s) References Examples

ggplot2_marginPlot function plots the percent change in number of DE genes identified at each step-wise increase in replicate level.

1	ggplot2_marginPlot(deg = NULL, stat = "median", path = ".", save_plot = TRUE)

`deg`	The list of DE genes generated by one of ERSSA::DE_*.R scripts.
`stat`	The statistic used for plotting. Options include 'mean', 'median'. Default='median'.
`path`	Path to which the plot will be saved. Default to current working directory.
`save_plot`	Boolean. Whether to save plot to drive. Default to TRUE.

The percent change is calculated as (margin*100 lower replicate level). The results are visualized as bar plots. Either mean or median can be used for the calculation.

A list is returned containing:

gg_object the ggplot2 object, which can then be further customized.
marg_diff.dataframe the tidy table version of percent changes for plotting.

Zixuan Shao, Zixuanshao.zach@gmail.com

H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2009.

# load edgeR deg object generated by erssa_edger using example dataset
# example dataset containing 1000 genes, 4 replicates and 5 comb. per rep.
# level
data(deg.partial, package = "ERSSA")

gg_margin = ggplot2_marginPlot(deg.partial)