MAplotW: MA-plot (Differential Intensity Versus Average Intensity)

In wrGraph: Graphics in the Context of Analyzing High-Throughput Data

MA-plot (Differential Intensity Versus Average Intensity)

Description

This type of plot for display of relative changes versus (mean) absolute abundance is very common in high-throughput biology, see MA-plot.

Usage

MAplotW(
  Mvalue,
  Avalue = NULL,
  useComp = 1,
  filtFin = NULL,
  tit = NULL,
  ProjNa = NULL,
  FCthrs = NULL,
  subTxt = NULL,
  grayIncrem = TRUE,
  col = NULL,
  pch = 16,
  compNa = NULL,
  batchFig = FALSE,
  cexMa = 1.8,
  cexLa = 1.1,
  limM = NULL,
  limp = NULL,
  annotColumn = c("SpecType", "GeneName", "EntryName", "Accession", "Species", "Contam"),
  annColor = NULL,
  expFCarrow = FALSE,
  cexPt = NULL,
  cexSub = NULL,
  cexTxLab = 0.7,
  namesNBest = NULL,
  NbestCol = 1,
  colBySpecType = FALSE,
  sortLeg = "descend",
  NaSpecTypeAsContam = TRUE,
  useMar = c(6.2, 4, 4, 2),
  returnData = FALSE,
  callFrom = NULL,
  silent = FALSE,
  debug = FALSE
)

Arguments

Mvalue	(numeric, list or MArrayLM-object) main data to plot; if numeric, the content will be used as M-values (and A-values must be provided separateley); if list or MArrayLM-object, it must conatin list-elements named Mvalue and means to extract all information needed for plotting
Avalue	(numeric, list or data.frame) if NULL it is assumed that A-values can be extracted form argument Mvalue
useComp	(integer) choice of one of multiple comparisons present in Mvalue (if generated using moderTestXgrp())
filtFin	(matrix or logical) The data may get filtered before plotting: If FALSE no filtering will get applied; if matrix of TRUE/FALSE it will be used as optional custom filter, otherwise (if Mvalue if an MArrayLM-object eg from limma) a default filtering based on the filtFin element will be applied
tit	(character) custom title
ProjNa	(character) add project-name to (automatic) title
FCthrs	(numeric) Fold-Change threshold (display as line) give as Fold-change and NOT log2(FC)
subTxt	(character) custom sub-title
grayIncrem	(logical) if TRUE, display overlay of points (not exceeding thresholds) as increased shades of gray
col	(character) custom color(s) for points of plot (see also par)
pch	(integer) type of symbol(s) to plot (default=16) (see also par)
compNa	(character) names of groups compared
batchFig	(logical) if TRUE figure title and axes legends will be kept shorter for display on fewer splace
cexMa	(numeric) font-size of title, as expansion factor (see also cex in par)
cexLa	(numeric) size of axis-labels, as expansion factor (see also cex in par)
limM	(numeric, length=2) range of axis M-values
limp	(numeric, length=2) range of axis FDR / p-values
annotColumn	(character) column names of annotation to be extracted (only if Mvalue is MArrayLM-object containing matrix $annot). The first entry (typically 'SpecType') is used for different symbols in figure, the second (typically 'GeneName') is used as prefered text for annotating the best points (if namesNBest allows to do so.)
annColor	(character or integer) colors for specific groups of annotation (only if Mvalue is MArrayLM-object containing matrix $annot)
expFCarrow	(logical, character or numeric) optional adding arrow for expected fold-change; if TRUE the expected ratio will be extracted from numeric concentration-indications from sample-names if numeric an arrow will be drawn (M-value as 1st position, color of 2nd position of vector).
cexPt	(numeric) size of points, as expansion factor (see also cex in par)
cexSub	(numeric) size of subtitle, as expansion factor (see also cex in par)
cexTxLab	(numeric) size of text-labels for points, as expansion factor (see also cex in par)
namesNBest	(integer or character) for display of labels to points in figure: if 'pass','passThr' or 'signif' all points passing thresholds; if numeric (length=1) this number of best points will get labels if the initial object Mvalue contains a list-element called 'annot' the second of the column specified in argument annotColumn will be used as text
NbestCol	(character or integer) colors for text-labels of best points, also used for arrow
colBySpecType	(logical) incase arument Mvalue is MArrayLM-object it is possible to use different color-codes for points passing thresholds based on Mvalue$annot[,"SpecType"]; use this with multi-species benchmark tests
sortLeg	(character) sorting of 'SpecType' annotation either ascending ('ascend') or descending ('descend'), no sorting if NULL
NaSpecTypeAsContam	(logical) consider lines/proteins with NA in Mvalue$annot[,"SpecType"] as contaminants (if a 'SpecType' for contaminants already exits)
useMar	(numeric, length=4) custom margings (see also par)
returnData	(logical) optional returning data.frame with (ID, Mvalue, pValue, FDRvalue, passFilt)
callFrom	(character) allow easier tracking of messages produced
silent	(logical) suppress messages
debug	(logical) additional messages for debugging

Details

Using an MMA-plot one compares two independent series of measures (ie gene transcript or protein abundance values) of 2 samples/data-sets or the means of 2 groups of replicates. Basically, the plot will dispaly a log-transformed ratio (log-fold-change) of both mesures ('Minus'=M) against the mean value of both mesures ('Average'=A). As with omics-data it is habit to with with log2-data, the ratio/fold-change can be obatined by subtraction this axis is also called 'Minus'=M) Furthermore, output from statistical testing by moderTest2grp or moderTestXgrp can be directly read to produce MA-plots, which are mriomarily used for diagnostic purposes. Please note, that plotting a very high number of points in transparency (eg >10000) may take several seconds.

Value

This function plots an MA-plot (to the current graphical device); if returnData=TRUE, a data.frame with ($ID, $Mvalue, $Avalue, $passFilt) gets returned

See Also

(for PCA) plotPCAw

Examples

library(wrMisc)
set.seed(2005); mat <- matrix(round(runif(600),2), ncol=6)
rownames(mat) <- paste(rep(letters[1:25],each=4), letters[2:26])
MAplotW(mat[,2] -mat[,1], A=rowMeans(mat[,1:2]))

## assume 2 groups with 3 samples each
matMeans <- rowGrpMeans(mat, gr=gl(2,3,labels=LETTERS[3:4]))
MAplotW(M=matMeans[,2] -matMeans[,1], A=rowMeans(mat)) 

## assume 2 groups with 3 samples each and run moderated t-test (from package 'limma')
tRes <- moderTest2grp(mat, gl(2,3))
MAplotW(tRes$Mval, tRes$Amean)                          
MAplotW(M=tRes$Mval, A=rowMeans(tRes$means), FCth=1.3) 
MAplotW(tRes)
MAplotW(tRes, limM=c(-2,2), FCth=1.3) 

wrGraph documentation built on June 11, 2026, 5:07 p.m.