correlate {granulator}R Documentation

Pearson correlation of cell type proportions across cell types and methods

Description

correlate computes Pearson correlations between estimated cell type proportions generated by different methods.

Usage

correlate(deconvoluted, scale = TRUE)

Arguments

deconvoluted

A list: output object from deconvolute

scale

Boolean: indicate whether the coefficients should be transformed to standard scores (default: scale = TRUE).

Details

correlation_analysis is particularly useful to assess the performance of the different methods when no ground truth is available. If several methods agree on similar relative abundances of cell types across samples, the results are more likely to reflect true differences in cell type composition.

Value

Returns a list encompassing two data frames:

Author(s)

Vincent Kuettel, Sabina Pfister

Examples

# load data
load_ABIS()

# deconvolute
decon <- deconvolute(m = bulkRNAseq_ABIS, 
sigMatrix = sigMatrix_ABIS_S0)

# correlate
correl <- correlate(deconvoluted = decon)


[Package granulator version 1.1.0 Index]