PlotProperty: Plot Distribution

Description Usage Arguments Value Author(s) Examples

Description

Plot biomarker or clinical variables properties.

Usage

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PlotProperty(data, biomarker.var, biomarker.class = NULL, var = NULL,
  var.class = NULL, log2 = FALSE, col = rgb(0, 0, 1, alpha = 0.3),
  add.num = 0, text.font = 3, main = "Distribution of", xlab = "",
  add.lab = "", border = NULL, add.cor = FALSE, cor.method = "spearman",
  lowess.line = FALSE, lowess.line.col = "deepskyblue",
  show.biomarker.uni = TRUE, show.clinical.uni = FALSE,
  show.association = TRUE, f = 0.3, las = 1, pdf.name = NULL,
  pdf.param = list(width = 6, height = 4.5), par.param = list(mar = c(4, 4,
  3, 2)), ...)

Arguments

data

input data frame. Rows are patients and columns are variables (e.g. demographics variables, time to event variables, biomarker variables, treatment indicator, etc.). One patient per row.

biomarker.var

name of the biomarker variable. Should be in colnames of data.

biomarker.class

can be either "numeric" or "categorical". If NULL (default), the class will be defined automatically.

var

name of a clinical variable. It can be a vector of variables. Should be in colnames of data. Default is NULL.

var.class

can be either "numeric" or "categorical". It can be a vector of classes. If NULL (default) and var is not NULL, then var.class will be defined automatically.

log2

if TRUE, computes binary (i.e. base 2) logarithm. It can be a vector if there are several numeric variables. The log2 transofrmation can be applied to numeric variables only. Default is FALSE.

col

the color of the line segments or dots. Default is "blue" with 30 percent transparency, i.e. rgb(0, 0, 1, alpha=0.3).

add.num

the constant to add to all values. Helps to avoid applying log transformation on 0 or negative values. Will be ignored if covariate is categorical. Default is 0.

text.font

legend text font size. Default is 3.

main

the main title. Default is "Distribution of".

xlab

x axis label. Default is "".

add.lab

an additional text to y axis label. Default is "".

border

a vector of colors for the outlines of the boxplots. Default is NULL.

add.cor

add the correlation coefficient to the boxplot. Default is FALSE.

cor.method

which correlation coefficient to compute. One of "pearson", "kendall", or "spearman" (default) can be abbreviated.

lowess.line

performs the computations for the LOWESS smoother which uses locally-weighted polynomial regression. See lowess.

lowess.line.col

the smoother color. Default is "deepskyblue".

show.biomarker.uni, show.clinical.uni, show.association

indicate whether to show biomarker uni-variate plot, clinical variable uni-variate plot, biomarker-clinical variable association plot, respectively. Default is TRUE for all but show.clinical.uni.

f

the smoother span. This gives the proportion of points in the plot which influence the smooth at each value. Larger values give more smoothness. Default is 0.3.

las

create a barplot with labels parallel (horizontal) to bars if las=2. Default is 1.

pdf.name

name of output pdf file. If it's NULL (default), the plots will be displayed but not saved as pdf.

pdf.param

a list of parameters that define pdf graphics device. See pdf. Default is list(width=6, height=4.5).

par.param

a list of parameters that define graphcial parameters. See par. Default is list(mar=c(4,4,3,2)).

...

other arguments passed on to the individual functions, like hist(), boxplot(), etc.

Value

If only a biomarker variable is given, it will crete a density plot for a numeric variable or bar plot for a categorical variable. If only a vactor of clinical variables is provided, it will create a density plot for each numeric variable and a bar plot for each categorical variable. If both a biomarker variable and a vector of clinical variables are given, it will create: a scatter plot for a numeric pair of variables; a bar plot for each categorical variable; a bar plot for a pair of categorical variables; a density plot for a numeric clinical variable; a boxplot for a pair of numeric and categorical variables.

Author(s)

Alexey Pronin [email protected], Ning Leng [email protected], and previous team members (see DESCRIPTION)

Examples

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data(input)
PlotProperty(data=input, biomarker.var="KRAS.exprs", biomarker.class="numeric", log2=TRUE)
PlotProperty(data=input, biomarker.var="KRAS.exprs", biomarker.class="numeric", log2=TRUE, breaks=5)
PlotProperty(data=input, biomarker.var="KRAS.exprs", biomarker.class="numeric", var="OS", var.class="numeric", log2=c(TRUE, FALSE))
PlotProperty(data=input, biomarker.var="KRAS.mutant", biomarker.class="categorical", var=c("Arm","OS"), var.class=c("categorical", "numeric"), par.param=list(mfrow=c(3, 2)))
PlotProperty(data=input, biomarker.var="KRAS.mutant", biomarker.class="categorical", var=c("Country", "Age"), var.class=c("categorical", "numeric"), col=rgb(0, 0, 1, 0.2), par.param=list(mfrow=c(3,2)))

lengning/gClinBiomarker documentation built on May 9, 2019, 2:55 p.m.