compareNormalizationD_HC: Builds a plot from a dataframe. Same as compareNormalizationD...

In samWieczorek/DAPAR: Tools for the Differential Analysis of Proteins Abundance with R

Builds a plot from a dataframe. Same as compareNormalizationD but uses the library highcharter

Description

Plot to compare the quantitative proteomics data before and after normalization using the library highcharter

Usage

compareNormalizationD_HC(
  qDataBefore,
  qDataAfter,
  keyId = NULL,
  conds = NULL,
  pal = NULL,
  subset.view = NULL,
  n = 100,
  type = "scatter"
)

Arguments

qDataBefore	A dataframe that contains quantitative data before normalization.
qDataAfter	A dataframe that contains quantitative data after normalization.
keyId	xxx
conds	A vector of the conditions (one condition per sample).
pal	xxx
subset.view	xxx
n	An integer that is equal to the maximum number of displayed points. This number must be less or equal to the size of the dataset. If it is less than it, it is a random selection
type	scatter or line

Value

A plot

Author(s)

Samuel Wieczorek

Examples

utils::data(Exp1_R25_prot, package='DAPARdata')
obj <- Exp1_R25_prot
qDataBefore <- Biobase::exprs(obj)
conds <- Biobase::pData(obj)[,"Condition"]
id <- Biobase::fData(obj)[,obj@experimentData@other$proteinId]
pal <- ExtendPalette(2)
objAfter <- wrapper.normalizeD(obj, method = "QuantileCentering", 
conds =conds, type = "within conditions")
compareNormalizationD_HC(qDataBefore=qDataBefore, 
qDataAfter=Biobase::exprs(objAfter), keyId = id, conds=conds, n=1000)

compareNormalizationD_HC(qDataBefore=qDataBefore, 
qDataAfter=Biobase::exprs(objAfter), keyId = id, pal=pal, subset.view=1:4, 
conds=conds, n=100)

samWieczorek/DAPAR documentation built on May 6, 2022, 5:30 p.m.