ggplot2_intersectPlot: Plot number of DE genes that is common across combinations
In ERSSA: Empirical RNA-seq Sample Size Analysis

Description Usage Arguments Details Value Author(s) References Examples

ggplot2_intersectPlot function generates and plots the list of differentially expressed (DE) genes that are found in all combinations at any particular replicate level. Often in small-scale RNA-seq experiments, the inclusion or exclusion of any paricular sample can result in a very different list of DE genes. To reduce the influence of any particular sample in the entire dataset analysis, it may be desirable to identify the list of DE genes that are enriched regardless of any specific sample(s) inclusion. This approach may be most useful analyzing the list of common DE genes at the greatest possible replicate to take advantage of the robust feature as well as employing typically the longest list of DE genes.

1	ggplot2_intersectPlot(deg = NULL, path = ".", save_plot = TRUE)

`deg`	The list of DE genes generated by one of ERSSA::DE_*.R scripts.
`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.

Similar to how increasing number of detected DE genes can be found with more biological replicates, the list of common DE genes is expected to increase with more replicates. This eventually levels off as majority of DE genes have been found.

A list is returned containing:

gg_object the ggplot2 object, which can then be further customized.
intersect.dataframe the tidy table version used for plotting.
deg_dataframe the tidy table version of DEG numbers for plotting mean.
intersect_genes list of vectors containing DE genes with vector name indicating the associated replicate level.
full_num_DEG The number of DE genes with all samples included.

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_intersect = ggplot2_intersectPlot(deg.partial)