multi.cor.var.compare: Calculates differential correlation statistics between a...

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

Description

Creates a table of pairwise correlations statistics, with separation of two groups for comparison. This can be used as an exploratory tool to investigate correlations between a specific variable of interest and all other variables within a separate dataset.

Usage

multi.cor.var.compare(variable, data1, data2, sample_col, group,
  ordered = "fisher")

Arguments

variable	character string indicating the variable of interest for differential correlation (within data1)
data1	first dataframe containing variable of interest
data2	second dataframe containing variable to compare
sample_col	character string defining the sample or identifying column in both datasets (common to both dataframes)
group	character string defining the grouping variable for comparative differential correlations
ordered	character string defining which column the table should be ordered by. Choose from g1cor, g1p, g2cor, g2r, fisher (default) and BH.

Value

a table (or dataframe) with Pearson correlation coefficients (r), associated p-values, fisher r-to-z statistic and BH p-value correlation for each correlation pair

Author(s)

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

Ben Day, [e-mail]

Examples

## Load example dataframes
df1 <- read.csv("example_data/excorr_df1.csv")
df2 <- read.csv("example_data/excorr_df2.csv")

## Run function
multi.cor.var.compare(variable = "NTRpFI", df1, df2, sample_col = "sample", group = "sex")
multi.cor.var.compare(variable = "NTRpFI", df1, df2, sample_col = "sample", group = "sex", ordered = "fisher")

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