Package index • BoutrosLab.plotting.general

All functions

CNA: Copy number aberration (CNA) data from colon cancer patients

SNV: Single nucleotide variant (SNV) data from colon cancer patients

auto.axis(): Create ideal labels and values for a given numeric vector (detects log scales)

colour.gradient(): Creates a colour gradient

covariates.grob(): Create one or more covariate bars

create.barplot(): Make a barplot

create.boxplot(): Make a boxplot

create.colourkey(): Create Colourkey

create.dendrogram(): Generate a dendrogram

create.densityplot(): Make a density plot

create.dotmap(): Make a dotmap with coloured background

create.gif(): Make a gif

create.heatmap(): Make a heatmap

create.hexbinplot(): Make a hexagonally binned plot

create.histogram(): Make a histogram

create.lollipopplot(): Make a lollipopplot

create.manhattanplot(): Make a Manhattan plot

create.multipanelplot(): Joins plots together

create.multiplot(): Joins plots together

create.polygonplot(): Make a polygonplot

create.qqplot.comparison(): Make a quantile-quantile plot of two samples

create.qqplot.fit(): Make a quantile-quantile plot of a sample

create.qqplot.fit.confidence.interval(): Create the confidence bands for a one-sample qq plot

create.scatterplot(): Make a scatterplot

create.segplot(): Make a segplot

create.stripplot(): Make a strip-plot

create.violinplot(): Make a violin plot

critical.value.ks.test(): Critical Value for Kolmogorov-Smirnov Test

default.colours(): Provides default colour schemes.

display.colours(): Function to display R colors, as well as corresponding R grey colours.

display.statistical.result(): Utility function to display statistical result in a plot

dist(): Distance Matrix Computation

force.colour.scheme(): Based on predefined colour schemes, returns a vector of corresponding colours.

generate.at.final(): Generates alternative default tick mark locations for create.densityplot() and create.scatterplot()

get.corr.key(): Correlation Key

get.correlation.p.and.corr(): Calculate a correlation and its statistical significance

get.defaults(): Get operating system specific default properties

get.line.breaks(): Get line breaks

legend.grob(): Generate a legend grob

microarray: Microarray dataset of colon cancer patients

panel.BL.bwplot: A lattice::panel.bwplot replacement that fixes colouring issues

patient: Dataset describing qualities of 58 colon cancer patients

pcawg.colours(): Return standard PCAWG colour palettes.

scientific.notation(): Use scientific notation in plots

show.available.palettes(): Display the available colour palettes

thousands.split(): Divide strings into groups of thousands

write.metadata(): Writes Metadata

write.plot(): Simplifies plotting by standardizing and centralizing all output-handling