spearmanPlot: Pairwise correlation coefficient plot
In lucyleeow/RPPA: Analyse RPPA Data From Zeptosens System

Description Usage Arguments Details Value

Calculate the pairwise Spearman correlation between all possible combinations of proteins and plot these (ordered) as a scatter plot.

1	spearmanPlot(tidydf, RFI1, RFI2)

`tidydf`	Tidy dataframe with RFI values, antibody names, sample names and any other optional columns.
`RFI1`	Name of the column of the RFI values to rank, as string.
`RFI2`	Optional argument. Name of the second column of RFI values to rank, as string.

This function performs the following steps:

For each protein, get the rank of it's expression level across all samples.
Get matrix of all possible pairs of proteins.
For each pair of proteins, calculate the Spearman correlation of their ranks.
Plot all the (ordered) Spearman correlations for all the protein pairs as a scatter plot.

The distribution of the correlations can be indicative of the performance of a normalisation technique. Differences in sample loading can result in artifically high correlations between protein pairs. You expect well normalised data to have similar positive and negative correlation coefficients. More information can be found in Liu et al..

Creates a plot in the current graphics device.

lucyleeow/RPPA documentation built on May 5, 2019, 3:46 a.m.