data.cor: Calculates differential correlation statistics for all the...

In emily5/exCorr: An R package for differential correlation analyses

Description

Creates a table of pairwise correlations statistics for all variables within a dataframe, with separation of two groups for comparison. This can be used as an exploratory tool to investigate differential correlations within a dataset. Requires grouping variable to compare two groups.

Usage

data.cor(data, group, ordered = "fisher", limit = NA)

Arguments

data	dataframe for analysis
group	character string defining the grouping variable for comparative differential correlations
ordered	character string defining the variable to order output by. Choose from g1cor, g1p, g2cor, g2r, fisher (default) and BH.
limit	numeric input to limit number of output correlation pairings

Value

a table (or dataframe) with correlation coefficients, p-values, fisher r-to-z p-value and adjusted p-value using Benjamini-Hochberg corretion for each correlation pair, with separation of two groups for comparison.

Author(s)

Emily Mears, [e-mail], Matthew Grant, [e-mail]

Ben Day, [e-mail]

Examples

## Load example dataframes
df <- read.csv("example_data/excorr_df2.csv")

## Run function
data.cor(df, group = "sex")
data.cor(df, group = "sex", ordered = "fisher", limit = 20)

emily5/exCorr documentation built on May 22, 2020, 1:01 p.m.