View source: R/plot_distribution.R
plot_variance_coefficients | R Documentation |
I want to look at the (B)CV of some data with respect to condition/batch/whatever. This function should make that possible, with some important caveats. The most appropriate metric is actually the biological coefficient of variation as calculated by DESeq2/EdgeR; but the metrics I am currently taking are the simpler and less appropriate CV(sd/mean) and QCD(q3-q1/q3+q1).
plot_variance_coefficients(
data,
design = NULL,
x_axis = "condition",
colors = NULL,
plot_title = NULL,
...
)
data |
Expressionset/epxt to poke at. |
design |
Specify metadata if necessary. |
x_axis |
Factor in the experimental design we may use to group the data and calculate the dispersion metrics. |
colors |
Set of colors to use when making the violins |
plot_title |
Optional title to include with the plot. |
... |
Extra arguments to pass along. |
List of plots showing the coefficients vs. genes along with the data.
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