norm_all: Normalise data
In lucyleeow/CellProfileR: Analyse Cell Morphology Data Generated By CellProfiler

Description Usage Arguments Value

View source: R/norm_all.R

Takes in CellProfiler morphology data and uses reshape::rescaler to normalise all data columns. Also calculates count value normalised to the negative control, for each plate, and retains the raw count value.

1 2	norm_all(df, data_cols, count_col = "Count_Cells", compound_col, negCtrl, rescale_type = "robust")

`df`	Dataframe containing the CellProfiler data to normalise.
`data_cols`	Numeric vector. Indicies of the data columns of df. All of these columns should be of numerice type. All remaining (non 'data_cols') should NOT be of numeric type.
`count_col`	Name of the column containing the raw cell counts, as string.
`compound_col`	Name of the column in 'df' containing the compound details.
`negCtrl`	Name of the negative control compound.
`rescale_type`	Type of rescaling to use, as string. Will be passed to `reshape::rescaler`.

A dataframe with the following columns, (in order):

Annotation columns (all non-data columns).
Cell count columns: raw cell count (the count_col column from df), cell count normalised to negative control, z score normalised cell count (using reshape::rescaler). The latter two columns are both calculated using the count_col column from df. Note that there should only be ONE count column. If df has more than one count column (e.g. 'count_cells' AND 'count_cells_unfiltered" columns), delete these such that only one remains.
All remaining data columns z score normalised (using reshape::rescaler). All of these columns names will be the same as the input dataframe.