ggeffectsize: visualization of effect size by the Linear Discriminant...

View source: R/plot-ggeffectsize.R

ggeffectsizeR Documentation

visualization of effect size by the Linear Discriminant Analysis or randomForest

Description

visualization of effect size by the Linear Discriminant Analysis or randomForest

Usage

ggeffectsize(obj, ...)

## S3 method for class 'data.frame'
ggeffectsize(
  obj,
  factorName,
  effectsizename,
  factorLevels = NULL,
  linecolor = "grey50",
  linewidth = 0.4,
  lineheight = 0.2,
  pointsize = 1.5,
  setFacet = TRUE,
  ...
)

## S3 method for class 'diffAnalysisClass'
ggeffectsize(obj, removeUnknown = TRUE, setFacet = TRUE, ...)

Arguments

obj

object, diffAnalysisClass see diff_analysis, or data.frame, contained effect size and the group information.

...

additional arguments.

factorName

character, the column name contained group information in data.frame.

effectsizename

character, the column name contained effect size information.

factorLevels

list, the levels of the factors, default is NULL, if you want to order the levels of factor, you can set this.

linecolor

character, the color of horizontal error bars, default is grey50.

linewidth

numeric, the width of horizontal error bars, default is 0.4.

lineheight

numeric, the height of horizontal error bars, default is 0.2.

pointsize

numeric, the size of points, default is 1.5.

setFacet

logical, whether use facet to plot, default is TRUE.

removeUnknown

logical, whether do not show unknown taxonomy, default is TRUE.

Value

the figures of effect size show the LDA or MDA (MeanDecreaseAccuracy).

Author(s)

Shuangbin Xu

Examples

## Not run: 
data(kostic2012crc)
kostic2012crc %<>% as.phyloseq()
head(phyloseq::sample_data(kostic2012crc),3)
kostic2012crc <- phyloseq::rarefy_even_depth(kostic2012crc,rngseed=1024)
table(phyloseq::sample_data(kostic2012crc)$DIAGNOSIS)
set.seed(1024)
diffres <- diff_analysis(kostic2012crc, classgroup="DIAGNOSIS",
                        mlfun="lda", filtermod="fdr",
                        firstcomfun = "kruskal.test",
                        firstalpha=0.05, strictmod=TRUE,
                        secondcomfun = "wilcox.test", 
                        subclmin=3, subclwilc=TRUE,
                        secondalpha=0.01, ldascore=3) 
library(ggplot2)
effectplot <- ggeffectsize(diffres) +
              scale_color_manual(values=c('#00AED7', 
                                          '#FD9347', 
                                          '#C1E168'))+
              theme_bw()+
              theme(strip.background=element_rect(fill=NA),
                    panel.spacing = unit(0.2, "mm"),
                    panel.grid=element_blank(),
                    strip.text.y=element_blank())

## End(Not run)

YuLab-SMU/MicrobiotaProcess documentation built on July 26, 2024, 4:21 a.m.