Hist: Compare Groups Based on Histograms

In statVisual: Statistical Visualization Tools

Description

Compare groups based on histograms.

Usage

Hist(
    data, 
    y, 
    group = NULL, 
    fill = group, 
    border.color = NULL, 
    inner.color = NULL, 
    theme_classic = TRUE, 
    bins = NULL, 
    binwidth = NULL, 
    alpha = 0.8, 
    xlab = y, 
    ylab = "count", 
    group.lab = group, 
    title = "Histogram", 
    addThemeFlag = TRUE,
    ...)

Arguments

data	A data frame. Rows are subjects; Columns are variables describing the subjects.
y	character. The column name of data that indicates the variable, for which the histogram will be drawn. The string y can also indicate a function of the variable, e.g., log(y).
group	character. The column name of data that indicates the subject groups. The histogram will be drawn for each of the subject group. It also indicates the border colors of the histograms.
fill	character. The column name of data that indicates the subject groups. It indicates the inside colors of the histograms.
border.color	Histogram border color, only available when group & fill are NULL.
inner.color	Histogram inside color, only available when group & fill are NULL.
theme_classic	logical. Use classic background without grids (default: TRUE).
bins	integer. number of bins of histogram (default: 30).
binwidth	Bin width of histogram.
alpha	Transparency of histogram inside color.
xlab	x axis label
ylab	y axis label
group.lab	label of group variable
title	title of the plot
addThemeFlag	logical. Indicates if light blue background and white grid should be added to the figure.
...	other input parameters for facet & theme

Value

A list with the following 9 elements. data, layers, scales, mapping, theme, coordinates, facet, plot_env, and labels.

Author(s)

Wenfei Zhang <[e-mail]>, Weiliang Qiu <[e-mail]>, Xuan Lin <[e-mail]>, Donghui Zhang <[e-mail]>

Examples

data(esSim)
print(esSim)

# expression data
dat = exprs(esSim)
print(dim(dat))
print(dat[1:2,])

# phenotype data
pDat = pData(esSim)
print(dim(pDat))
print(pDat[1:2,])

# feature data
fDat = fData(esSim)
print(dim(fDat))
print(fDat[1:2,])

# choose the first probe which is over-expressed in cases
pDat$probe1 = dat[1,]

# check histograms of probe 1 expression in cases and controls
print(table(pDat$grp, useNA = "ifany"))

statVisual(type = 'Hist', 
       data = pDat, 
       y = 'probe1', 
       group = 'grp') 

Hist(
     data = pDat, 
     y = 'probe1', 
     group = 'grp') 

statVisual documentation built on Feb. 21, 2020, 1:08 a.m.