compareNormalizationD_HC {DAPAR} | R Documentation

## 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,
      palette = 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).
`palette` | 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]
    objAfter <- wrapper.normalizeD(obj, method = "QuantileCentering", conds =conds, type = "within conditions")
    compareNormalizationD_HC(qDataBefore=qDataBefore, qDataAfter=Biobase::exprs(objAfter), keyId = id, conds=conds, n=100)

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

[Package DAPAR version 1.22.9 Index]