ggforest: forest plot base ggplot2 with the result of RunPoolEffect and...

In xiangpin/MetaMicrobiome: An R package for meta-analysis and visualization of Microbiome.

Description

Polt a forest with the result of RunPoolEffect and multiVarRRTab base-on the ggplot.

Usage

ggforest(dataset, manualcolors, manualshapes, Logscale = TRUE, x, y,
  lower, upper, pointsize = 2, linesize = 0.4, errorbarhheight = 0.2,
  colorVar, shapeVar, facetx = NULL, facety = NULL, xlabs, ylabs,
  setTheme = TRUE)

Arguments

dataset	dataframe; a dataframe of result of RunPoolEffect and multiVarRRTab
manualcolors	character; the ponit colors.
manualshapes	character; the point shape.
Logscale	logical; log2 for x-axis (default) or not?
x	character; the header name in the dataframe for map to axes of point.
y	character; the header name in the dataframe for map to ayes of point.
lower	character; the header name in the dataframe for map to lower of the errorbar.
upper	character; the header name in the dataframe for map to upper of the errorbar.
pointsize	numeric; the point size, default is 3.0 .
linesize	numeric; the errorbar line size, default is 0.4 .
errorbarhheight	numeric; the errorbar height size, default is 0.2 .
colorVar	character; the header name in the dataframe for map to the color of point.
shapeVar	character; the header name in the dataframe for map to the shape of point.
facetx	character; the header name in the dataframe for map to the facet of row, default is NULL.
facety	character; the header name in the dataframe for map to the facet of col, default is NULL.
xlabs	character; label for the x-axis.
ylabs	character; label for the y-axis.
setTheme	logical; whether set the default theme.

Details

TODO

Value

Returns a ggplot object.

Author(s)

Shuangbin Xu

Examples

library("MetaMicrobiome")
data <- system.file("data", package="MetaMicrobiome", "ggforestDemo.rda")
load(data)
head(ggforestDemoData)
ggforestDemoData$study <- factor(ggforestDemoData$study, 
                               levels=rev(unique(ggforestDemoData$study)))
print(levels(ggforestDemoData$study))
pointcolors <- rev(c("#E41A1C",
                     "#4DAF4A", 
		    "#984EA3", 
		    "#FF7F00", 
		    "#FFFF33", 
		    "#A65628",
		    "#F781BF",
		    "#999999"))
pointshape <- c(18, 20)
data1 <- ggforestDemoData[ggforestDemoData$measure=="Shannon",]
head(data1)
data2 <- ggforestDemoData
head(data2)
p1 <- ggforest(dataset=data1,
      manualcolors=pointcolors,
      manualshapes=pointshape,
      x="est",
      y="study",
      Logscale=TRUE,
      lower="lower",
      upper="upper",
      colorVar="study",
      shapeVar="unite",
      pointsize=3,
      linesize=0.4,
      errorbarhheight=0.05,
      xlabs="Odds Ratio",
      ylabs="",
      setTheme=TRUE)

p2 <- ggforest(dataset=data2,
         manualcolors=pointcolors,
         manualshapes=pointshape,
         x="est",
         y="study",
         Logscale=TRUE,
         lower="lower",
         upper="upper",
         colorVar="study",
         shapeVar="unite",
         pointsize=3,
         linesize=0.4,
         errorbarhheight=0.05,
         xlabs="Odds Ratio",
         ylabs="",
         facetx="measure",
         facety="group",
         setTheme=TRUE)

xiangpin/MetaMicrobiome documentation built on May 26, 2019, 2:34 a.m.