metricsCorrelations: Calculation of Pearson correlation coefficient.

In evaluomeR: Evaluation of Bioinformatics Metrics

Description

Calculation of Pearson correlation coefficient between every pair of metrics available in order to quantify their interrelationship degree. The score is in the range [-1,1]. Perfect correlations: -1 (inverse), and 1 (direct).

Usage

metricsCorrelations(data, margins = c(0, 10, 9, 11), getImages = TRUE)

Arguments

data	A SummarizedExperiment. The SummarizedExperiment must contain an assay with the following structure: A valid header with names. The first column of the header is the ID or name of the instance of the dataset (e.g., ontology, pathway, etc.) on which the metrics are measured. The other columns of the header contains the names of the metrics. The rows contains the measurements of the metrics for each instance in the dataset.
margins	See par.
getImages	Boolean. If true, a plot is displayed.

Value

The Pearson correlation matrix as an assay in a SummarizedExperiment object.

Examples

# Using example data from our package
data("ontMetrics")
cor = metricsCorrelations(ontMetrics, getImages = TRUE, margins = c(1,0,5,11))

evaluomeR documentation built on March 15, 2021, 6 p.m.