genefilter: filter_volcano – R documentation

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filter_volcano

Volcano plot for overall variance filtering

Description

Generate a volcano plot contrasting p-value with fold change (on the log scale), in order to visualize the effect of filtering on overall variance and also assign significance via p-value.

Usage

filter_volcano(
               d, p, S,
               n1, n2,
               alpha, S_cutoff,
               cex = 0.5, pch = 19,
               xlab = expression(paste(log[2], " fold change")),
               ylab = expression(paste("-", log[10], " p")),
               cols = c("grey80", "grey50", "black"),
               ltys = c(1, 3),
               use_legend = TRUE,
               ...
               )

Arguments

`d`	Fold changes, typically on the log scale, base 2.
`p`	The p-values
`S`	The overall standard deviation filter statistics, i.e., the square roots of the overall variance filter statistics.
`n1`	Sample size for group 1.
`n2`	Sample size for group 2.
`alpha`	Significance cutoff used for p-values.
`S_cutoff`	Filter cutoff used for the overall standard deviation in `S`.
`cex`	Point size for plotting.
`pch`	Point character for plotting.
`xlab`	Label for x-axis.
`ylab`	Label for y-axis.
`cols`	A vector of three colors used for plotting. These correspond to filtered data, data which pass the filter but are insignificant, and data pass the filter and are also statistically significant.
`ltys`	The induced bound on log-scale fold change is plotted, as is the significance cutoff for data passing the filter. The `ltys` argument gives line styles for these drawing these two thresholds on the plot.
`use_legend`	Should a legend for point color be produced?
`...`	Other arguments for `plot`.

Author(s)

Richard Bourgon <bourgon@ebi.ac.uk>

Examples

# See the vignette: Diagnostic plots for independent filtering

genefilter

genefilter: methods for filtering genes from high-throughput experiments

v1.72.1

Artistic-2.0

Authors

R. Gentleman, V. Carey, W. Huber, F. Hahne

Initial release