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Quantitative trait locus study design from an information perspective
S Sen, JM Satagopan, and GA Churchill

Disclaimer The source code and software distributed in this web page has no implied warranty. Use at your own risk.

Symbolic computation code Some of the results in the paper were derived using symbolic calculations in Maxima. Start Maxima in your system, and then you can cut and paste the contents of the files below into the command window. The files are commented, so you should be able to follow the steps.

• Formula for missing information in backcross: bc-missing.max
• Calculating the determinant and inverse of the information matrix for F₂'s: f2det.max
• Formula for missing information in backcross in the presence of a second QTL, assuming that first QTL has small effect: 2qtl.max

Figures

• Figure 1: genopat.m; this uses Pseudomarker version 0.9 written in Matlab, and the salt-induced hypertension data from Sugiyama et.al. (2001)
• Figure 2: chr4.R; this uses the R/qtl package
• Figure 3: numerical.R
• Figures 4 and 5: optimal.R
• Figure 6: opt-alpha.R; this uses the R/qtlDesign package version 0.32 (see below).
• Figure 7: replication.R
• Figure 8: 2qtl.R

R/qtlDesign This package performs power calculations and minimum effect size determinations for backcross and F₂ intercross populations. These calculations take into account selective genotyping of the extreme phenotypic individuals and marker spacing. It is an add-on package to the R programming language. To install version 0.32 of the package (in UNIX or OS X) download the file qtlDesign_0.32.tar.gz, and give the type in a command window:

   R CMD INSTALL qtlDesign_0.32.tar.gz

...last updated 13 july 2005...