Skip to contents

DiffZeroOne: Assessing the Z-score for deviation from one and zero.

Source: R/GXwasR_main_functions.R
DiffZeroOne.Rd

This function tests the null hypothesis that a measured statistics (example: genetic correlation, rg for a trait) < 1 using a 1-tailed test compared with a normal distribution (z = (1 − measure statistics)/Standard error). For multiple tests, users are encouraged to apply a Bonferroni multiple-testing correction.

Usage

DiffZeroOne(inputdata, diffzero = TRUE, diffone = TRUE)

Arguments

inputdata

A dataframe object, containing three columns:

  • Trait (i.e., the phenotype of interest)

  • Stat (i.e., the measured statistics)

  • SE (i.e., the standard error of the measured statistics)

diffzero

Boolean value, TRUE or FALSE, specifying to perform deviation from 0 test.

diffone

Boolean value, TRUE or FALSE, specifying to perform deviation from 1 test.

Value

A dataframe with columns:

  • Trait

  • Stat

  • SE

  • P0 (i.e, p-value for deviation from zero test)

  • P1 (i.e., p-value for deviation from 1 test)

Examples

data("Example_rgdata", package = "GXwasR")
inputdata <- Example_rgdata
colnames(inputdata) <- c("Trait", "Stat", "SE")
x <- DiffZeroOne(inputdata, FALSE, TRUE)