.plotQuantDistr {wrProteo}

Generic plotting of density distribution for quantitation import-functions

Description

This (low-level) function allows (generic) plotting of density distribution for quantitation import-functions

Usage

.plotQuantDistr(
  abund,
  quant,
  custLay = NULL,
  normalizeMeth = NULL,
  softNa = NULL,
  refLi = NULL,
  refLiIni = NULL,
  notLogAbund = NA,
  figMarg = c(3.5, 3.5, 3, 1),
  tit = NULL,
  las = NULL,
  cexAxis = 0.8,
  nameSer = NULL,
  cexNameSer = NULL,
  silent = FALSE,
  callFrom = NULL,
  debug = FALSE
)

Arguments

abund

(matrix or data.frame) abundance data, will be plottes as distribution

quant

(matrix or data.frame) optional additional abundance data, to plot 2nd distribution, eg of normalized data

custLay

(matrix) describing sammple-setup, typically produced by

normalizeMeth

(character, length=1) name of normalization method (will be displayed in title of figure)

softNa

(character, length=1) name of quantitation-software (typically 2-letter abbreviation, eg 'MQ')

refLi

(integer) to display number reference lines

refLiIni

(integer) to display initial number reference lines

notLogAbund

(logical) set to TRUE if abund is linear but should be plotted as log2

figMarg

(numeric, length=4) custom figure margins (will be passed to par), defaults to c(3.5, 3.5, 3, 1)

tit

(character) custom title

las

(integer) indicate orientation of text in axes

cexAxis

(numeric) size of numeric axis labels as cex-expansion factor (see also par)

nameSer

(character) custom label for data-sets or columns (length must match number of data-sets)

cexNameSer

(numeric) size of individual data-series labels as cex-expansion factor (see also par)

silent

(logical) suppress messages

callFrom

(character) allow easier tracking of messages produced

debug

(logical) display additional messages for debugging

Value

This function returns logical value (if data were valid for plotting) and produces a density dustribution figure (if data were found valid)

See Also

used in readProtDiscovererFile, readMaxQuantFile, readProlineFile, readFragpipeFile

Examples

set.seed(2018);  datT8 <- matrix(round(rnorm(800) +3,1), nc=8, dimnames=list(paste(
  "li",1:100,sep=""), paste(rep(LETTERS[1:3],c(3,3,2)),letters[18:25],sep="")))
.plotQuantDistr(datT8, quant=NULL, refLi=NULL, tit="Synthetic Data Distribution")