View source: R/filter_volcano.R
filter_volcano | R Documentation |
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.
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,
...
)
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 |
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 |
use_legend |
Should a legend for point color be produced? |
... |
Other arguments for |
Richard Bourgon <bourgon@ebi.ac.uk>
# See the vignette: Diagnostic plots for independent filtering
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