| Information {qtlDesign} | R Documentation |
Information under null hypothesis of equal means
Description
Functions to calculate the information under the null hypothesis of no effect. Functions for discount factors for incomplete genotyping.
Usage
info(sel.frac,theta=0,cross)
info.bc(sel.frac,theta=0)
info.f2(sel.frac,theta=0)
deflate(theta,cross)
deflate.bc(theta)
deflate.f2(theta)
nullinfo(sel.frac)
Arguments
cross |
Cross type, either "bc" for backcross, or "f2" for intercross. |
sel.frac |
Selection fraction; proportion of extremes genotyped |
theta |
Recombination fraction between flanking markers |
Details
The nullinfo function calculates the information
content per observation for any contrast between genotype means when
densely genotyping an sel.frac fraction of
the extreme phenotypic individuals. The information content is
calculated under the null hypothesis of no difference between the
genotype means. For small differences in genotype means, the
information content will be approximately equal to the null, but in
general, the information estimate under the null is the lower bound.
The info function calculates the information per observation
for backcross, and F2 intercross under the null hypothesis of equal
gentoype means. The information is calculated for a point in the
middle of an interval spanned by markers separated by a recombination
fraction theta. The function deflate calculates a
deflation factor for the information attenuation in the middle of a
marker interval relative to a completely typed location.
Value
Information per individual for information functions, and the discount factor for the discount functions.
Note
Information is calculated under the equal means assumption. This approximation is very good in practice, and is slightly conservative. If the difference between the means is large, these functions will underestimate the information. For power calculations, that is okay.
Author(s)
Saunak Sen, Jaya Satagopan, Karl Broman, and Gary Churchill
References
Sen S, Satagopan JM, Churchill GA (2005) Quantitative trait locus study design from an information perspective. Genetics, 170:447-64.
Examples
nullinfo(0.5)
info(0.5,cross="bc")
info(0.5,cross="f2")
info(0.5,0.1,cross="bc")
info(0.5,0.1,cross="f2")
deflate(0.1,"bc")
deflate(0.1,"f2")