In previous work, a modified version of the Bayesian information criterion (mBIC) was proposed to locate multiple interacting quantitative trait loci (QTL). Simulation studies and real data analysis demonstrate good properties of the mBIC in situations where the error distribution is approximately normal. However, as with other standard techniques of QTL mapping, the performance of the mBIC str...

4. The best way to get help on the functions and data sets in R (and in R/qtl) is via the html version of the help files. One way to get access to this is to type help.start() This should open a browser with the main help menu. If you then click on Packages→ qtl, you can see all of the available functions and datasets in R/qtl. For example, look at the help file for the function read.cross. An ...

When censored time-to-event data are used to map quantitative trait loci (QTL), the existence of nonsusceptible subjects entails extra challenges. If the heterogeneous susceptibility is ignored or inappropriately handled, we may either fail to detect the responsible genetic factors or find spuriously significant locations. In this article, an interval mapping method based on parametric mixture ...

A starting point . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 add.cim.covar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 add.threshold . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 addcovarint . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 addint . ...