check.trait: function to do primitive trait quality control

In GenABEL: genome-wide SNP association analysis

Description

This function check for outliers (using FDR framework) and plots the raw data.

Usage

check.trait(trait, data, fdrate = 0.05, graph = TRUE, binshow = FALSE, 
		qoption = "bh95")

Arguments

trait	name (or list of names) of trait(s) to be checked
data	gwaa.data object or data frame containing the trait
fdrate	false discovery rate to apply for QC
graph	if graphical output should be produced
binshow	if binary traits should be plotted
qoption	how to compute q-values (not implemented, currently using only BH95)

Details

The P-value that a particulat measurment is an outlier is compted as folowing. Consider trait vector Y with particulat i^{th} measurment denodet as y_i. Let Y(-i) is vector, which is the same as Y, except that i^{th} measurment is dropped. Then Chi-square for measurment i is computed as

Chi_{i} = (mean(Y(-i)) - y_i)^2/var(Y(-i))

P-value is computed using 1 d.f., and the vector of P-values enters FDR computation procedure (BH95 by default).

Value

No value returned, output is made to the screen and graphical device.

Author(s)

Yurii Aulchenko

See Also

check.marker

Examples

require(GenABEL.data)
data(srdta)
check.trait("qt3",data=srdta)
n <- names(srdta@phdata)
check.trait(n,data=srdta)

GenABEL documentation built on May 30, 2017, 3:36 a.m.